%%% -*-BibTeX-*- %%% ==================================================================== %%% BibTeX-file{ %%% author = "Nelson H. F. Beebe", %%% version = "1.06", %%% date = "30 April 2024", %%% time = "13:25:27 MST", %%% filename = "tompecs.bib", %%% address = "University of Utah %%% Department of Mathematics, 110 LCB %%% 155 S 1400 E RM 233 %%% Salt Lake City, UT 84112-0090 %%% USA", %%% telephone = "+1 801 581 5254", %%% FAX = "+1 801 581 4148", %%% URL = "http://www.math.utah.edu/~beebe", %%% checksum = "51939 6317 33955 321036", %%% email = "beebe at math.utah.edu, beebe at acm.org, %%% beebe at computer.org (Internet)", %%% codetable = "ISO/ASCII", %%% keywords = "ACM Transactions on Modeling and Performance %%% Evaluation of Computing Systems (TOMPECS); %%% bibliography; BibTeX", %%% license = "public domain", %%% supported = "yes", %%% docstring = "This is a COMPLETE BibTeX bibliography for %%% ACM Transactions on Modeling and Performance %%% Evaluation of Computing Systems (TOMPECS) %%% (CODEN ????, ISSN 2376-3639 (print), %%% 2376-3647 (electronic)). The journal appears %%% quarterly, and publication began with volume %%% 1, number 1, in March 2016. %%% %%% At version 1.06, the COMPLETE journal %%% coverage looked like this: %%% %%% 2016 ( 26) 2019 ( 23) 2022 ( 7) %%% 2017 ( 17) 2020 ( 14) 2023 ( 12) %%% 2018 ( 22) 2021 ( 20) 2024 ( 8) %%% %%% Article: 149 %%% %%% Total entries: 149 %%% %%% The journal Web page can be found at: %%% %%% http://tompecs.acm.org/ %%% %%% The journal table of contents page is at: %%% %%% http://dl.acm.org/pub.cfm?id=J1525 %%% https://dl.acm.org/loi/tompecs %%% %%% Qualified subscribers can retrieve the full %%% text of recent articles in PDF form. %%% %%% The initial draft was extracted from the ACM %%% Web pages. %%% %%% ACM copyrights explicitly permit abstracting %%% with credit, so article abstracts, keywords, %%% and subject classifications have been %%% included in this bibliography wherever %%% available. Article reviews have been %%% omitted, until their copyright status has %%% been clarified. %%% %%% bibsource keys in the bibliography entries %%% below indicate the entry originally came %%% from the computer science bibliography %%% archive, even though it has likely since %%% been corrected and updated. %%% %%% URL keys in the bibliography point to %%% World Wide Web locations of additional %%% information about the entry. %%% %%% BibTeX citation tags are uniformly chosen %%% as name:year:abbrev, where name is the %%% family name of the first author or editor, %%% year is a 4-digit number, and abbrev is a %%% 3-letter condensation of important title %%% words. Citation tags were automatically %%% generated by software developed for the %%% BibNet Project. %%% %%% In this bibliography, entries are sorted in %%% publication order, using ``bibsort -byvolume.'' %%% %%% The checksum field above contains a CRC-16 %%% checksum as the first value, followed by the %%% equivalent of the standard UNIX wc (word %%% count) utility output of lines, words, and %%% characters. This is produced by Robert %%% Solovay's checksum utility.", %%% } %%% ==================================================================== @Preamble{"\input bibnames.sty" # "\def \TM {${}^{\sc TM}$}" } %%% ==================================================================== %%% Acknowledgement abbreviations: @String{ack-nhfb = "Nelson H. F. Beebe, University of Utah, Department of Mathematics, 110 LCB, 155 S 1400 E RM 233, Salt Lake City, UT 84112-0090, USA, Tel: +1 801 581 5254, FAX: +1 801 581 4148, e-mail: \path|beebe@math.utah.edu|, \path|beebe@acm.org|, \path|beebe@computer.org| (Internet), URL: \path|http://www.math.utah.edu/~beebe/|"} %%% ==================================================================== %%% Journal abbreviations: @String{j-TOMPECS = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)"} %%% ==================================================================== %%% Bibliography entries: @Article{Towsley:2016:I, author = "Don Towsley and Carey Williamson", title = "Introduction", journal = j-TOMPECS, volume = "1", number = "1", pages = "1:1--1:1", month = mar, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2893179", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:29:10 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2893179", acknowledgement = ack-nhfb, articleno = "1", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Lashgar:2016:ESM, author = "Ahmad Lashgar and Amirali Baniasadi", title = "Employing Software-Managed Caches in {OpenACC}: Opportunities and Benefits", journal = j-TOMPECS, volume = "1", number = "1", pages = "2:1--2:34", month = mar, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2798724", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:29:10 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2798724", abstract = "The OpenACC programming model has been developed to simplify accelerator programming and improve development productivity. In this article, we investigate the main limitations faced by OpenACC in harnessing all capabilities of GPU-like accelerators. We build on our findings and discuss the opportunity to exploit a software-managed cache as (i) a fast communication medium and (ii) a cache for data reuse. To this end, we propose a new directive and communication model for OpenACC. Investigating several benchmarks, we show that the proposed directive can improve performance up to $ 2.54 \times $, and at the cost of minor programming effort.", acknowledgement = ack-nhfb, articleno = "2", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Zhang:2016:VSL, author = "Deli Zhang and Jeremiah Wilke and Gilbert Hendry and Damian Dechev", title = "Validating the Simulation of Large-Scale Parallel Applications Using Statistical Characteristics", journal = j-TOMPECS, volume = "1", number = "1", pages = "3:1--3:22", month = mar, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2809778", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:29:10 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2809778", abstract = "Simulation is a widely adopted method to analyze and predict the performance of large-scale parallel applications. Validating the hardware model is highly important for complex simulations with a large number of parameters. Common practice involves calculating the percent error between the projected and the real execution time of a benchmark program. However, in a high-dimensional parameter space, this coarse-grained approach often suffers from parameter insensitivity, which may not be known a priori. Moreover, the traditional approach cannot be applied to the validation of software models, such as application skeletons used in online simulations. In this work, we present a methodology and a toolset for validating both hardware and software models by quantitatively comparing fine-grained statistical characteristics obtained from execution traces. Although statistical information has been used in tasks like performance optimization, this is the first attempt to apply it to simulation validation. Our experimental results show that the proposed evaluation approach offers significant improvement in fidelity when compared to evaluation using total execution time, and the proposed metrics serve as reliable criteria that progress toward automating the simulation tuning process.", acknowledgement = ack-nhfb, articleno = "3", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Roos:2016:DDE, author = "Stefanie Roos and Thorsten Strufe", title = "Dealing with Dead Ends: Efficient Routing in Darknets", journal = j-TOMPECS, volume = "1", number = "1", pages = "4:1--4:30", month = mar, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2809779", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:29:10 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2809779", abstract = "Darknets, membership-concealing peer-to-peer networks, suffer from high message delivery delays due to insufficient routing strategies. They form topologies restricted to a subgraph of the social network of their users by limiting connections to peers with a mutual trust relationship in real life. Whereas centralized, highly successful social networking services entail a privacy loss of their users, Darknets at higher performance represent an optimal private and censorship-resistant communication substrate for social applications. Decentralized routing so far has been analyzed under the assumption that the network resembles a perfect lattice structure. Freenet, currently the only widely used Darknet, attempts to approximate this structure by embedding the social graph into a metric space. Considering the resulting distortion, the common greedy routing algorithm is adapted to account for local optima. Yet the impact of the adaptation has not been adequately analyzed. We thus suggest a model integrating inaccuracies in the embedding. In the context of this model, we show that the Freenet routing algorithm cannot achieve polylog performance. Consequently, we design NextBestOnce, a provable poylog algorithm based only on information about neighbors. Furthermore, we show that the routing length of NextBestOnce is further decreased by more than a constant factor if neighbor-of-neighbor information is included in the decision process.", acknowledgement = ack-nhfb, articleno = "4", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Izagirre:2016:STA, author = "A. Izagirre and U. Ayesta and I. M. Verloop", title = "Sojourn Time Approximations for a Discriminatory Processor Sharing Queue", journal = j-TOMPECS, volume = "1", number = "1", pages = "5:1--5:31", month = mar, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2812807", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:29:10 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2812807", abstract = "We study a multiclass time-sharing discipline with relative priorities known as discriminatory processor sharing (DPS), which provides a natural framework to model service differentiation in systems. The analysis of DPS is extremely challenging, and analytical results are scarce. We develop closed-form approximations for the mean conditional (on the service requirement) and unconditional sojourn times. The main benefits of the approximations lie in its simplicity, the fact that it applies for general service requirements with finite second moments, and that it provides insights into the dependency of the performance on the system parameters. We show that the approximation for the mean conditional and unconditional sojourn time of a customer is decreasing as its relative priority increases. We also show that the approximation is exact in various scenarios, and that it is uniformly bounded in the second moments of the service requirements. Finally, we numerically illustrate that the approximation for exponential, hyperexponential, and Pareto service requirements is accurate across a broad range of parameters.", acknowledgement = ack-nhfb, articleno = "5", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Harrison:2016:EPT, author = "Peter G. Harrison and Naresh M. Patel and William J. Knottenbelt", title = "Energy--Performance Trade-Offs via the {EP} Queue", journal = j-TOMPECS, volume = "1", number = "2", pages = "6:1--6:31", month = jun, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2818726", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:54 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2818726", abstract = "We introduce the EP queue -- a significant generalization of the M B / G /1 queue that has state-dependent service time probability distributions and incorporates power-up for first arrivals and power-down for idle periods. We derive exact results for the busy-time and response-time distributions. From these, we derive power consumption metrics during nonidle periods and overall response time metrics, which together provide a single measure of the trade-off between energy and performance. We illustrate these trade-offs for some policies and show how numerical results can provide insights into system behavior. The EP queue has application to storage systems, especially hard disks, and other data-center components such as compute servers, networking, and even hyperconverged infrastructure.", acknowledgement = ack-nhfb, articleno = "6", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Tavakkol:2016:PED, author = "Arash Tavakkol and Pooyan Mehrvarzy and Mohammad Arjomand and Hamid Sarbazi-Azad", title = "Performance Evaluation of Dynamic Page Allocation Strategies in {SSDs}", journal = j-TOMPECS, volume = "1", number = "2", pages = "7:1--7:33", month = jun, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2829974", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:54 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2829974", abstract = "Solid-state drives (SSDs) with tens of NAND flash chips and highly parallel architectures are widely used in enterprise and client storage systems. As any write operation in NAND flash is preceded by a slow erase operation, an out-of-place update mechanism is used to distribute writes through SSD storage space to postpone erase operations as far as possible. SSD controllers use a mapping table along with a specific allocation strategy to map logical host addresses to physical page addresses within storage space. The allocation strategy is further responsible for accelerating I/O operations through better striping of physical addresses over SSD parallel resources. Proposals already exist for using static logical-to-physical address mapping that does not balance the I/O traffic load within the SSD, and its efficiency highly depends on access patterns. A more balanced distribution of I/O operations is to alternate resource allocation in a round-robin manner irrespective of logical addresses. The number of resources that can be dynamically allocated in this fashion is defined as the degree of freedom, and to the best of our knowledge, there has been no research thus far to show what happens if different degrees of freedom are used in allocation strategy. This article explores the possibility of using dynamic resource allocation and identifies key design opportunities that it presents to improve SSD performance. Specifically, using steady-state analysis of SSDs, we show that dynamism helps to mitigate performance and endurance overheads of garbage collection. Our steady-state experiments indicate that midrange/high-end SSDs with dynamic allocation can provide I/O operations per second (IOPS) improvement of up to 3.3x/9.6x, response time improvement of up to 56\%/32\%, and about 88\%/96\% average reduction in the standard deviation of erase counts of NAND flash blocks.", acknowledgement = ack-nhfb, articleno = "7", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Chang:2016:CRA, author = "Cheng-Shang Chang and Jay Cheng and Tien-Ke Huang and Duan-Shin Lee and Cheng-Yu Chen", title = "Coding Rate Analysis of Forbidden Overlap Codes in High-Speed Buses", journal = j-TOMPECS, volume = "1", number = "2", pages = "8:1--8:25", month = jun, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2846091", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:54 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2846091", abstract = "One of the main problems in deep submicron designs of high-speed buses is propagation delay due to the crosstalk effect. To alleviate the crosstalk effect, there are several types of crosstalk avoidance codes proposed in the literature. In this article, we analyze the coding rates of forbidden overlap codes (FOCs) that avoid ``010 $ \to $ 101'' transition and ``101 $ \to $ 010'' transition on any three adjacent wires in a bus. We first compute the maximum achievable coding rate of FOCs and the maximum coding rate of memoryless FOCs. Our numerical results show that there is a significant gap between the maximum coding rate of memoryless FOCs and the maximum achievable rate. We then analyze the coding rates of FOCs generated from the bit-stuffing algorithm. Our worst-case analysis yields a tight lower bound of the coding rate of the bit-stuffing algorithm. Under the assumption of Bernoulli inputs, we use a Markov chain model to compute the coding rate of a bus with n wires under the bit-stuffing algorithm. The main difficulty of solving such a Markov chain model is that the number of states grows exponentially with respect to the number of wires n. To tackle the problem of the curse of dimensionality, we derive an approximate analysis that leads to a recursive closed-form formula for the coding rate over the n th wire. Our approximations match extremely well with the numerical results from solving the original Markov chain for $ n \leq 10 $ and the simulation results for $ n \leq 3000 $. Our analysis of coding rates of FOCs could be helpful in understanding the trade-off between propagation delay and coding rate among various crosstalk avoidance codes in the literature. In comparison with the forbidden transition codes (FTCs) that have shorter propagation delay than that of FOCs, our numerical results show that the coding rates of FOCs are much higher than those of FTCs.", acknowledgement = ack-nhfb, articleno = "8", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Bermolen:2016:ETP, author = "Paola Bermolen and Matthieu Jonckheere and Federico Larroca and Pascal Moyal", title = "Estimating the Transmission Probability in Wireless Networks with Configuration Models", journal = j-TOMPECS, volume = "1", number = "2", pages = "9:1--9:23", month = jun, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2858795", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:54 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2858795", abstract = "We propose a new methodology to estimate the probability of successful transmissions for random access scheduling in wireless networks, in particular those using Carrier Sense Multiple Access (CSMA). Instead of focusing on spatial configurations of users, we model the interference between users as a random graph. Using configuration models for random graphs, we show how the properties of the medium access mechanism are captured by some deterministic differential equations when the size of the graph gets large. Performance indicators such as the probability of connection of a given node can then be efficiently computed from these equations. We also perform simulations to illustrate the results on different types of random graphs. Even on spatial structures, these estimates get very accurate as soon as the variance of the interference is not negligible.", acknowledgement = ack-nhfb, articleno = "9", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Yan:2016:PAF, author = "Feng Yan and Xenia Mountrouidou and Alma Riska and Evgenia Smirni", title = "{PREFiguRE}: An Analytic Framework for {HDD} Management", journal = j-TOMPECS, volume = "1", number = "3", pages = "10:1--10:27", month = may, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2872331", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:54 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2872331", abstract = "Low disk drive utilization suggests that placing the drive into a power saving mode during idle times may decrease power consumption. We present PREFiguRE, a robust framework that aims at harvesting future idle intervals for power savings while meeting strict quality constraints: first, it contains potential delays in serving IO requests that occur during power savings since the time to bring up the disk is not negligible, and second, it ensures that the power saving mechanism is triggered a few times only, such that the disk wear-out due to powering up and down does not compromise the disk's lifetime. PREFiguRE is based on an analytic methodology that uses the histogram of idle times to determine schedules for power saving modes as a function of the preceding constraints. PREFiguRE facilitates analysis for the evaluation of the trade-offs between power savings and quality targets for the current workload. Extensive experimentation on a set of enterprise storage traces illustrates PREFiguRE's effectiveness to consistently achieve high power savings without undermining disk reliability and performance.", acknowledgement = ack-nhfb, articleno = "10", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Antunes:2016:EFD, author = "Nelson Antunes and Vladas Pipiras", title = "Estimation of Flow Distributions from Sampled Traffic", journal = j-TOMPECS, volume = "1", number = "3", pages = "11:1--11:28", month = may, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2891106", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:54 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2891106", abstract = "This work addresses the problem of estimating the distributions of packet flow sizes and durations under several methods of sampling packets. Two approaches, one based on inversion and the other on asymptotics, are considered. For the duration distribution, in particular, both approaches require modeling the structure of flows, with the duration distribution being characterized in terms of the IATs (interarrival times between packets) and size distributions of a flow. The inversion of the flow IAT distribution from sampled flow quantities, along with the inversion of the flow size distribution (already used in the literature) allows estimating the flow duration distribution. Motivated by the limitations of the inversion approach in estimating the distribution tails for some sampling methods, an asymptotic approach is developed to estimate directly the distribution tails of flow durations and sizes from sampled quantities. The adequacy of both approaches to estimate the flow distributions is checked against two real Internet traces.", acknowledgement = ack-nhfb, articleno = "11", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Garetto:2016:UAP, author = "Michele Garetto and Emilio Leonardi and Valentina Martina", title = "A Unified Approach to the Performance Analysis of Caching Systems", journal = j-TOMPECS, volume = "1", number = "3", pages = "12:1--12:28", month = may, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2896380", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:54 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2896380", abstract = "We propose a unified methodology to analyze the performance of caches (both isolated and interconnected), by extending and generalizing a decoupling technique originally known as Che's approximation, which provides very accurate results at low computational cost. We consider several caching policies (including a very attractive one, called k -LRU), taking into account the effects of temporal locality. In the case of interconnected caches, our approach allows us to do better than the Poisson approximation commonly adopted in prior work. Our results, validated against simulations and trace-driven experiments, provide interesting insights into the performance of caching systems.", acknowledgement = ack-nhfb, articleno = "12", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Xie:2016:DAI, author = "Hong Xie and John C. S. Lui and Don Towsley", title = "Design and Analysis of Incentive and Reputation Mechanisms for Online Crowdsourcing Systems", journal = j-TOMPECS, volume = "1", number = "3", pages = "13:1--13:27", month = may, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2897510", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:54 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2897510", abstract = "Today, online crowdsourcing services like Amazon Mechanical Turk, UpWork, and Yahoo! Answers are gaining in popularity. For such online services, it is important to attract ``workers'' to provide high-quality solutions to the ``tasks'' outsourced by ``requesters.'' The challenge is that workers have different skill sets and can provide different amounts of effort. In this article, we design a class of incentive and reputation mechanisms to solicit high-quality solutions from workers. Our incentive mechanism allows multiple workers to solve a task, splits the reward among workers based on requester evaluations of the solution quality, and guarantees that high-skilled workers provide high-quality solutions. However, our incentive mechanism suffers the potential risk that a requester will eventually collects low-quality solutions due to fundamental limitations in task assigning accuracy. Our reputation mechanism ensures that low-skilled workers do not provide low-quality solutions by tracking workers' historical contributions and penalizing those workers having poor reputations. We show that by coupling our reputation mechanism with our incentive mechanism, a requester can collect at least one high-quality solution. We present an optimization framework to select parameters for our reputation mechanism. We show that there is a trade-off between system efficiency (i.e., the number of tasks that can be solved for a given reward) and revenue (i.e., the amount of transaction fees), and we present the optimal trade-off curve between system efficiency and revenue. We demonstrate the applicability and effectiveness of our mechanisms through experiments using a real-world dataset from UpWork. We infer model parameters from this data, use them to determine proper rewards, and select the parameters of our incentive and reputation mechanisms for UpWork. Experimental results show that our incentive and reputation mechanisms achieve 98.82\% of the maximum system efficiency while only sacrificing 4\% of revenue.", acknowledgement = ack-nhfb, articleno = "13", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Ghaderi:2016:SSS, author = "Javad Ghaderi and Sanjay Shakkottai and R. Srikant", title = "Scheduling Storms and Streams in the Cloud", journal = j-TOMPECS, volume = "1", number = "4", pages = "14:1--14:28", month = sep, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2904080", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:55 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2904080", abstract = "Motivated by emerging big streaming data processing paradigms (e.g., Twitter Storm, Streaming MapReduce), we investigate the problem of scheduling graphs over a large cluster of servers. Each graph is a job, where nodes represent compute tasks and edges indicate data flows between these compute tasks. Jobs (graphs) arrive randomly over time and, upon completion, leave the system. When a job arrives, the scheduler needs to partition the graph and distribute it over the servers to satisfy load balancing and cost considerations. Specifically, neighboring compute tasks in the graph that are mapped to different servers incur load on the network; thus a mapping of the jobs among the servers incurs a cost that is proportional to the number of ``broken edges.'' We propose a low-complexity randomized scheduling algorithm that, without service preemptions, stabilizes the system with graph arrivals/departures; more importantly, it allows a smooth tradeoff between minimizing average partitioning cost and average queue lengths. Interestingly, to avoid service preemptions, our approach does not rely on a Gibbs sampler; instead, we show that the corresponding limiting invariant measure has an interpretation stemming from a loss system.", acknowledgement = ack-nhfb, articleno = "14", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Papadopoulos:2016:PPE, author = "Alessandro Vittorio Papadopoulos and Ahmed Ali-Eldin and Karl-Erik {\AA}rz{\'e}n and Johan Tordsson and Erik Elmroth", title = "{PEAS}: A Performance Evaluation Framework for Auto-Scaling Strategies in Cloud Applications", journal = j-TOMPECS, volume = "1", number = "4", pages = "15:1--15:31", month = sep, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2930659", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:55 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2930659", abstract = "Numerous auto-scaling strategies have been proposed in the past few years for improving various Quality of Service (QoS) indicators of cloud applications, for example, response time and throughput, by adapting the amount of resources assigned to the application to meet the workload demand. However, the evaluation of a proposed auto-scaler is usually achieved through experiments under specific conditions and seldom includes extensive testing to account for uncertainties in the workloads and unexpected behaviors of the system. These tests by no means can provide guarantees about the behavior of the system in general conditions. In this article, we present a Performance Evaluation framework for Auto-Scaling (PEAS) strategies in the presence of uncertainties. The evaluation is formulated as a chance constrained optimization problem, which is solved using scenario theory. The adoption of such a technique allows one to give probabilistic guarantees of the obtainable performance. Six different auto-scaling strategies have been selected from the literature for extensive test evaluation and compared using the proposed framework. We build a discrete event simulator and parameterize it based on real experiments. Using the simulator, each auto-scaler's performance is evaluated using 796 distinct real workload traces from projects hosted on the Wikimedia foundations' servers, and their performance is compared using PEAS. The evaluation is carried out using different performance metrics, highlighting the flexibility of the framework, while providing probabilistic bounds on the evaluation and the performance of the algorithms. Our results highlight the problem of generalizing the conclusions of the original published studies and show that based on the evaluation criteria, a controller can be shown to be better than other controllers.", acknowledgement = ack-nhfb, articleno = "15", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Fricker:2016:AOS, author = "Christine Fricker and Fabrice Guillemin and Philippe Robert and Guilherme Thompson", title = "Analysis of an Offloading Scheme for Data Centers in the Framework of Fog Computing", journal = j-TOMPECS, volume = "1", number = "4", pages = "16:1--16:18", month = sep, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2950047", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:55 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2950047", abstract = "In the context of fog computing, we consider a simple case where data centers are installed at the edge of the network and assume that if a request arrives at an overloaded data center, then it is forwarded to a neighboring data center with some probability. Data centers are assumed to have a large number of servers, and traffic at some of them is assumed to cause saturation. In this case, the other data centers may help to cope with this saturation regime by accepting some of the rejected requests. Our aim is to qualitatively estimate the gain achieved via cooperation between neighboring data centers. After proving some convergence results related to the scaling limits of loss systems for the process describing the number of free servers at both data centers, we show that the performance of the system can be expressed in terms of the invariant distribution of a random walk in the quarter plane. By using and developing existing results in the technical literature, explicit formulas for the blocking rates of such a system are derived.", acknowledgement = ack-nhfb, articleno = "16", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{DeCicco:2016:CTA, author = "Luca {De Cicco} and Yixi Gong and Dario Rossi and Emilio Leonardi", title = "A Control-Theoretic Analysis of Low-Priority Congestion Control Reprioritization under {AQM}", journal = j-TOMPECS, volume = "1", number = "4", pages = "17:1--17:33", month = sep, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2934652", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:55 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2934652", abstract = "Recently, a negative interplay has been shown to arise when scheduling/Active Queue Management (AQM) techniques and low-priority congestion control protocols are used together; namely, AQM resets the relative level of priority among congestion control protocols. This work explores this issue by carrying out a control-theoretic analysis of the dynamical system to prove some fundamental properties that fully characterize the reprioritization phenomenon. In particular, (i) we provide the closed-form solution of the equilibrium in the open loop (i.e., fixing a target loss probability p ); (ii) we provide a stability analysis and a characterization of the reprioritization phenomenon when closing the loop with AQM (i.e., that dynamically adjusts the system loss probability). Our results are important as the characterization of the reprioritization phenomenon is not only quantitatively accurate for the specific protocols and AQM considered but also qualitatively accurate for a broader range of congestion control protocol and AQM combinations. Finally, while we find a sufficient condition to avoid the reprioritization phenomenon, we also show, at the same time, such conditions to be likely impractical: Therefore, we propose a simple and practical system-level solution that is able to reinstate priorities among protocols.", acknowledgement = ack-nhfb, articleno = "17", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Zhang:2016:TIM, author = "Linquan Zhang and Shaolei Ren and Chuan Wu and Zongpeng Li", title = "A Truthful Incentive Mechanism for Emergency Demand Response in Geo-Distributed Colocation Data Centers", journal = j-TOMPECS, volume = "1", number = "4", pages = "18:1--18:23", month = sep, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2950046", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:55 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2950046", abstract = "Data centers are key participants in demand response programs, including emergency demand response (EDR), in which the grid coordinates consumers of large amounts of electricity for demand reduction in emergency situations to prevent major economic losses. While existing literature concentrates on owner-operated data centers, this work studies EDR in geo-distributed multitenant colocation data centers in which servers are owned and managed by individual tenants. EDR in colocation data centers is significantly more challenging due to lack of incentives to reduce energy consumption by tenants who control their servers and are typically on fixed power contracts with the colocation operator. Consequently, to achieve demand reduction goals set by the EDR program, the operator has to rely on the highly expensive and/or environmentally unfriendly on-site energy backup/generation. To reduce cost and environmental impact, an efficient incentive mechanism is therefore needed, motivating tenants' voluntary energy reduction in the case of EDR. This work proposes a novel incentive mechanism, Truth-DR, which leverages a reverse auction to provide monetary remuneration to tenants according to their agreed energy reduction. Truth-DR is computationally efficient, truthful, and achieves 2-approximation in colocation-wide social cost. Trace-driven simulations verify the efficacy of the proposed auction mechanism.", acknowledgement = ack-nhfb, articleno = "18", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Fu:2016:FPP, author = "Yongquan Fu and Ernst Biersack", title = "False-Positive Probability and Compression Optimization for Tree-Structured {Bloom} Filters", journal = j-TOMPECS, volume = "1", number = "4", pages = "19:1--19:39", month = sep, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2940324", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:55 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/datacompression.bib; http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2940324", abstract = "Bloom filters are frequently used to to check the membership of an item in a set. However, Bloom filters face a dilemma: the transmission bandwidth and the accuracy cannot be optimized simultaneously. This dilemma is particularly severe for transmitting Bloom filters to remote nodes when the network bandwidth is limited. We propose a novel Bloom filter called BloomTree that consists of a tree-structured organization of smaller Bloom filters, each using a set of independent hash functions. BloomTree spreads items across levels that are compressed to reduce the transmission bandwidth need. We show how to find optimal configurations for BloomTree and investigate in detail by how much BloomTree outperforms the standard Bloom filter or the compressed Bloom filter. Finally, we use the intersection of BloomTrees to predict the set intersection, decreasing the false-positive probabilities by several orders of magnitude compared to both the compressed Bloom filter and the standard Bloom filter.", acknowledgement = ack-nhfb, articleno = "19", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Anonymous:2016:LR, author = "Anonymous", title = "List of Reviewers", journal = j-TOMPECS, volume = "1", number = "4", pages = "20:1--20:2", month = sep, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2989212", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:55 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2989212", acknowledgement = ack-nhfb, articleno = "20", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Molka:2016:CAW, author = "Karsten Molka and Giuliano Casale", title = "Contention-Aware Workload Placement for In-Memory Databases in Cloud Environments", journal = j-TOMPECS, volume = "2", number = "1", pages = "1:1--1:29", month = nov, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2961888", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:55 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2961888", abstract = "Big data processing is driven by new types of in-memory database systems. In this article, we apply performance modeling to efficiently optimize workload placement for such systems. In particular, we propose novel response time approximations for in-memory databases based on fork-join queuing models and contention probabilities to model variable threading levels and per-class memory occupation under analytical workloads. We combine these approximations with a nonlinear optimization methodology that seeks optimal load dispatching probabilities in order to minimize memory swapping and resource utilization. We compare our approach with state-of-the-art response time approximations using real data from an SAP HANA in-memory system and show that our models markedly improve accuracy over existing approaches, at similar computational costs.", acknowledgement = ack-nhfb, articleno = "1", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Vergara:2016:FIC, author = "Ekhiotz Jon Vergara and Simin Nadjm-Tehrani and Mikael Asplund", title = "Fairness and Incentive Considerations in Energy Apportionment Policies", journal = j-TOMPECS, volume = "2", number = "1", pages = "2:1--2:29", month = nov, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2970816", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:55 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2970816", abstract = "The energy consumption of a system is determined by the system component usage patterns and interactions between the coexisting entities and resources. Energy accounting plays an essential role in revealing the contribution of each entity to the total consumption and for energy management. Unfortunately, energy accounting inherits the apportionment problem of accounting in general, which does not have a general single best solution. In this article, we leverage cooperative game theory, which is commonly used in cost allocation problems to study the energy apportionment problem, that is, the problem of prescribing the actual energy consumption of a system to the consuming entities (e.g., applications, processes, or users of the system). We identify five relevant fairness properties for energy apportionment and present a detailed categorisation and analysis of eight previously proposed energy apportionment policies from different fields in computer and communication systems. In addition, we propose two novel energy apportionment policies based on cooperative game theory that provide strong fairness notion and a rich incentive structure. Our comparative analysis in terms of the identified five fairness properties as well as information requirement and computational complexity shows that there is a tradeoff between fairness and the other evaluation criteria. We provide guidelines to select an energy apportionment policy depending on the purpose of the apportionment and the characteristics of the system.", acknowledgement = ack-nhfb, articleno = "2", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Nasiriani:2016:FAC, author = "Neda Nasiriani and Cheng Wang and George Kesidis and Bhuvan Urgaonkar and Lydia Y. Chen and Robert Birke", title = "On Fair Attribution of Costs Under Peak-Based Pricing to Cloud Tenants", journal = j-TOMPECS, volume = "2", number = "1", pages = "3:1--3:28", month = nov, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2970815", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:55 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2970815", abstract = "The costs incurred by cloud providers towards operating their data centers are often determined in large part by their peak demands. The pricing schemes currently used by cloud providers to recoup these costs from their tenants, however, do not distinguish tenants based on their contributions to the cloud's overall peak demand. Using the concrete example of peak-based pricing as employed by many electric utility companies, we show that this ``gap'' may lead to unfair attribution of costs to the tenants. Simple enhancements of existing cloud pricing (e.g., analogous to the coincident peak pricing (CPP) used by some electric utilities) do not adequately address these shortcomings and suffer from short-term unfairness and undesirable oscillatory price-vs.-demand relationships offered to tenants. To overcome these shortcomings, we define an alternative pricing scheme to more fairly distribute a cloud's costs among its tenants. We demonstrate the efficacy of our scheme under price-sensitive tenant demand response using a combination of (i) extensive empirical evaluation with recent workloads from commercial data centers operated by IBM and (ii) analytical [modeling] through non-cooperative game theory for a special case of tenant demand model.", acknowledgement = ack-nhfb, articleno = "3", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Nain:2016:FDD, author = "Philippe Nain and Don Towsley", title = "File Dissemination in Dynamic Graphs: The Case of Independent and Correlated Links in Series", journal = j-TOMPECS, volume = "2", number = "1", pages = "4:1--4:23", month = nov, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2981344", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:55 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2981344", abstract = "In this article, we investigate the traversal time of a file across N communication links subject to stochastic changes in the sending rate of each link. Each link's sending rate is modeled by a finite-state Markov process. Two cases, one where links evolve independently of one another ( N mutually independent Markov processes) and the second where their behaviors are dependent (these N Markov processes are not mutually independent), are considered. A particular instance where the above is encountered is ad hoc delay/tolerant networks where links are subject to intermittent unavailability.", acknowledgement = ack-nhfb, articleno = "4", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Liu:2016:SSS, author = "Qingyun Liu and Xiaohan Zhao and Walter Willinger and Xiao Wang and Ben Y. Zhao and Haitao Zheng", title = "Self-Similarity in Social Network Dynamics", journal = j-TOMPECS, volume = "2", number = "1", pages = "5:1--5:26", month = nov, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2994142", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:55 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2994142", abstract = "Analyzing and modeling social network dynamics are key to accurately predicting resource needs and system behavior in online social networks. The presence of statistical scaling properties, that is, self-similarity, is critical for determining how to model network dynamics. In this work, we study the role that self-similarity scaling plays in a social network edge creation (that is, links created between users) process, through analysis of two detailed, time-stamped traces, a 199 million edge trace over 2 years in the Renren social network, and 876K interactions in a 4-year trace of Facebook. Using wavelet-based analysis, we find that the edge creation process in both networks is consistent with self-similarity scaling, once we account for periodic user activity that makes edge creation process non-stationary. Using these findings, we build a complete model of social network dynamics that combines temporal and spatial components. Specifically, the temporal behavior of our model reflects self-similar scaling properties, and accounts for certain deterministic non-stationary features. The spatial side accounts for observed long-term graph properties, such as graph distance shrinkage and local declustering. We validate our model against network dynamics in Renren and Facebook datasets, and show that it succeeds in producing desired properties in both temporal patterns and graph structural features.", acknowledgement = ack-nhfb, articleno = "5", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Krishnasamy:2016:DSR, author = "Subhashini Krishnasamy and Rajat Sen and Sanjay Shakkottai and Sewoong Oh", title = "Detecting Sponsored Recommendations", journal = j-TOMPECS, volume = "2", number = "1", pages = "6:1--6:29", month = nov, year = "2016", CODEN = "????", DOI = "https://doi.org/10.1145/2988543", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:55 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2988543", abstract = "With the vast number of items, Web pages, and news from which to choose, online services and customers both benefit tremendously from personalized recommender systems. Such systems additionally provide great opportunities for targeted advertisements by displaying ads alongside genuine recommendations. We consider a biased recommendation system in which such ads are displayed without any tags (disguised as genuine recommendations), rendering them indistinguishable to a single user. We ask whether it is possible for a small subset of collaborating users to detect such bias. We propose an algorithm that can detect this type of bias through statistical analysis on the collaborating users' feedback. The algorithm requires only binary information indicating whether a user was satisfied with each of the recommended item or not. This makes the algorithm widely appealing to real-world issues such as identification of search engine bias and pharmaceutical lobbying. We prove that the proposed algorithm detects the bias with high probability for a broad class of recommendation systems when a sufficient number of users provides feedback on a sufficient number of recommendations. We provide extensive simulations with real datasets and practical recommender systems, which confirm the trade-offs in the theoretical guarantees.", acknowledgement = ack-nhfb, articleno = "6", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Petsas:2017:MMA, author = "Thanasis Petsas and Antonis Papadogiannakis and Michalis Polychronakis and Evangelos P. Markatos and Thomas Karagiannis", title = "Measurement, Modeling, and Analysis of the Mobile App Ecosystem", journal = j-TOMPECS, volume = "2", number = "2", pages = "7:1--7:33", month = may, year = "2017", CODEN = "????", DOI = "https://doi.org/10.1145/2993419", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:56 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=2993419", abstract = "Mobile applications (apps) have been gaining popularity due to the advances in mobile technologies and the large increase in the number of mobile users. Consequently, several app distribution platforms, which provide a new way for developing, downloading, and updating software applications in modern mobile devices, have recently emerged. To better understand the download patterns, popularity trends, and development strategies in this rapidly evolving mobile app ecosystem, we systematically monitored and analyzed four popular third-party Android app marketplaces. Our study focuses on measuring, analyzing, and modeling the app popularity distribution and explores how pricing and revenue strategies affect app popularity and developers' income. Our results indicate that unlike web and peer-to-peer file sharing workloads, the app popularity distribution deviates from commonly observed Zipf-like models. We verify that these deviations can be mainly attributed to a new download pattern, which we refer to as the clustering effect. We validate the existence of this effect by revealing a strong temporal affinity of user downloads to app categories. Based on these observations, we propose a new formal clustering model for the distribution of app downloads and demonstrate that it closely fits measured data. Moreover, we observe that paid apps follow a different popularity distribution than free apps and show how free apps with an ad-based revenue strategy may result in higher financial benefits than paid apps. We believe that this study can be useful to appstore designers for improving content delivery and recommendation systems, as well as to app developers for selecting proper pricing policies to increase their income.", acknowledgement = ack-nhfb, articleno = "7", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Yi:2017:CDC, author = "Xiaomeng Yi and Fangming Liu and Di Niu and Hai Jin and John C. S. Lui", title = "{Cocoa}: Dynamic Container-Based Group Buying Strategies for Cloud Computing", journal = j-TOMPECS, volume = "2", number = "2", pages = "8:1--8:31", month = may, year = "2017", CODEN = "????", DOI = "https://doi.org/10.1145/3022876", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:56 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib; http://www.math.utah.edu/pub/tex/bib/virtual-machines.bib", URL = "http://dl.acm.org/citation.cfm?id=3022876", abstract = "Although the Infrastructure-as-a-Service (IaaS) cloud offers diverse instance types to users, a significant portion of cloud users, especially those with small and short demands, cannot find an instance type that exactly fits their needs or fully utilize purchased instance-hours. In the meantime, cloud service providers are also faced with the challenge to consolidate small, short jobs, which exhibit strong dynamics, to effectively improve resource utilization. To handle such inefficiencies and improve cloud resource utilization, we propose Cocoa (COmputing in COntAiners), a novel group buying mechanism that organizes jobs with complementary resource demands into groups and allocates them to group buying deals predefined by cloud providers. Each group buying deal offers a resource pool for all the jobs in the deal, which can be implemented as either a virtual machine or a physical server. By running each user job on a virtualized container, our mechanism allows flexible resource sharing among different users in the same group buying deal, while improving resource utilization for cloud providers. To organize jobs with varied resource demands and durations into groups, we model the initial static group organization as a variable-sized vector bin packing problem, and the subsequent dynamic group organization problem as an online multidimensional knapsack problem. Through extensive simulations driven by a large amount of real usage traces from a Google cluster, we evaluate the potential cost reduction achieved by Cocoa. We show that through the effective combination and interaction of the proposed static and dynamic group organization strategies, Cocoa greatly outperforms the existing cloud workload consolidation mechanism, substantiating the feasibility of group buying in cloud computing.", acknowledgement = ack-nhfb, articleno = "8", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Liu:2017:ECE, author = "Yu-Hang Liu and Xian-He Sun", title = "Evaluating the Combined Effect of Memory Capacity and Concurrency for Many-Core Chip Design", journal = j-TOMPECS, volume = "2", number = "2", pages = "9:1--9:25", month = may, year = "2017", CODEN = "????", DOI = "https://doi.org/10.1145/3038915", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:56 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=3038915", abstract = "Modern memory systems are structured under hierarchy and concurrency. The combined impact of hierarchy and concurrency, however, is application dependent and difficult to describe. In this article, we introduce C 2 -Bound, a data-driven analytical model that serves the purpose of optimizing many-core design. C 2 -Bound considers both memory capacity and data access concurrency. It utilizes the combined power of the newly proposed latency model, concurrent average memory access time, and the well-known memory-bounded speedup model (Sun-Ni's law) to facilitate computing tasks. Compared to traditional chip designs that lack the notion of memory capacity and concurrency, the C 2 -Bound model finds that memory bound factors significantly impact the optimal number of cores as well as their optimal silicon area allocations, especially for data-intensive applications with a non-parallelizable sequential portion. Therefore, our model is valuable to the design of next-generation many-core architectures that target big data processing, where working sets are usually larger than the conventional scientific computing. These findings are evidenced by our detailed simulations, which show, with C 2 -Bound, the design space of chip design can be narrowed down significantly up to four orders of magnitude. C 2 -Bound analytic results can be either used in reconfigurable hardware environments or, by software designers, applied to scheduling, partitioning, and allocating resources among diverse applications.", acknowledgement = ack-nhfb, articleno = "9", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Simhon:2017:ARG, author = "Eran Simhon and David Starobinski", title = "Advance Reservation Games", journal = j-TOMPECS, volume = "2", number = "2", pages = "10:1--10:21", month = may, year = "2017", CODEN = "????", DOI = "https://doi.org/10.1145/3053046", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:56 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=3053046", abstract = "Advance reservation (AR) services form a pillar of several branches of the economy, including transportation, lodging, dining, and, more recently, cloud computing. In this work, we use game theory to analyze a slotted AR system in which customers differ in their lead times. For each given time slot, the number of customers requesting service is a random variable following a general probability distribution. Based on statistical information, the customers decide whether or not to make an advance reservation of server resources in future slots for a fee. We prove that only two types of equilibria are possible: either none of the customers makes AR or only customers with lead time greater than some threshold make AR. Our analysis further shows that the fee that maximizes the provider's profit may lead to other equilibria, one of which yields zero profit. In order to prevent ending up with no profit, the provider can elect to advertise a lower fee yielding a guaranteed but smaller profit. We refer to the ratio of the maximum possible profit to the maximum guaranteed profit as the price of conservatism. When the number of customers is a Poisson random variable, we prove that the price of conservatism is one in the single-server case, but can be arbitrarily high in a many-server system.", acknowledgement = ack-nhfb, articleno = "10", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Kelley:2017:OMA, author = "Jaimie Kelley and Christopher Stewart and Nathaniel Morris and Devesh Tiwari and Yuxiong He and Sameh Elnikety", title = "Obtaining and Managing Answer Quality for Online Data-Intensive Services", journal = j-TOMPECS, volume = "2", number = "2", pages = "11:1--11:31", month = may, year = "2017", CODEN = "????", DOI = "https://doi.org/10.1145/3055280", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:56 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=3055280", abstract = "Online data-intensive (OLDI) services use anytime algorithms to compute over large amounts of data and respond quickly. Interactive response times are a priority, so OLDI services parallelize query execution across distributed software components and return best effort answers based on the data so far processed. Omitted data from slow components could lead to better answers, but tracing online how much better the answers could be is difficult. We propose Ubora, a design approach to measure the effect of slow-running components on the quality of answers. Ubora randomly samples online queries and executes them a second time. The first online execution omits data from slow components and provides interactive answers. The second execution uses mature results from intermediate components completed after the online execution finishes. Ubora uses memoization to speed up mature executions by replaying network messages exchanged between components. Our systems-level implementation works for a wide range of services, including Hadoop/Yarn, Apache Lucene, the EasyRec Recommendation Engine, and the OpenEphyra question-answering system. Ubora computes answer quality with more mature executions per second than competing approaches that do not use memoization. With Ubora, we show that answer quality is effective at guiding online admission control. While achieving the same answer quality on high-priority queries, our adaptive controller had 55\% higher peak throughput on low-priority queries than a competing controller guided by the rate of timeouts.", acknowledgement = ack-nhfb, articleno = "11", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Joshi:2017:ERT, author = "Gauri Joshi and Emina Soljanin and Gregory Wornell", title = "Efficient Redundancy Techniques for Latency Reduction in Cloud Systems", journal = j-TOMPECS, volume = "2", number = "2", pages = "12:1--12:30", month = may, year = "2017", CODEN = "????", DOI = "https://doi.org/10.1145/3055281", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Jun 15 12:19:56 MDT 2017", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "http://dl.acm.org/citation.cfm?id=3055281", abstract = "In cloud computing systems, assigning a task to multiple servers and waiting for the earliest copy to finish is an effective method to combat the variability in response time of individual servers and reduce latency. But adding redundancy may result in higher cost of computing resources, as well as an increase in queueing delay due to higher traffic load. This work helps in understanding when and how redundancy gives a cost-efficient reduction in latency. For a general task service time distribution, we compare different redundancy strategies in terms of the number of redundant tasks and the time when they are issued and canceled. We get the insight that the log-concavity of the task service time creates a dichotomy of when adding redundancy helps. If the service time distribution is log-convex (i.e., log of the tail probability is convex), then adding maximum redundancy reduces both latency and cost. And if it is log-concave (i.e., log of the tail probability is concave), then less redundancy, and early cancellation of redundant tasks is more effective. Using these insights, we design a general redundancy strategy that achieves a good latency-cost trade-off for an arbitrary service time distribution. This work also generalizes and extends some results in the analysis of fork-join queues.", acknowledgement = ack-nhfb, articleno = "12", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Du:2017:SCB, author = "Yuhuan Du and Gustavo {De Veciana}", title = "Scheduling for Cloud-Based Computing Systems to Support Soft Real-Time Applications", journal = j-TOMPECS, volume = "2", number = "3", pages = "13:1--13:??", month = sep, year = "2017", CODEN = "????", DOI = "https://doi.org/10.1145/3063713", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:14 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3063713", abstract = "Cloud-based computing infrastructure provides an efficient means to support real-time processing workloads, for example, virtualized base station processing, and collaborative video conferencing. This article addresses resource allocation for a computing system with multiple resources supporting heterogeneous soft real-time applications subject to Quality of Service (QoS) constraints on failures to meet processing deadlines. We develop a general outer bound on the feasible QoS region for non-clairvoyant resource allocation policies and an inner bound for a natural class of policies based on dynamically prioritizing applications' tasks by favoring those with the largest (QoS) deficits. This provides an avenue to study the efficiency of two natural resource allocation policies: (1) priority-based greedy task scheduling for applications with variable workloads and (2) priority-based task selection and optimal scheduling for applications with deterministic workloads. The near-optimality of these simple policies emerges when task processing deadlines are relatively large and/or when the number of compute resources is large. Analysis and simulations show substantial resource savings for such policies over reservation-based designs.", acknowledgement = ack-nhfb, articleno = "13", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Dong:2017:CAT, author = "Fang Dong and Kui Wu and Venkatesh Srinivasan", title = "Copula Analysis of Temporal Dependence Structure in {Markov} Modulated {Poisson} Process and Its Applications", journal = j-TOMPECS, volume = "2", number = "3", pages = "14:1--14:??", month = sep, year = "2017", CODEN = "????", DOI = "https://doi.org/10.1145/3089254", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:14 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3089254", abstract = "The Markov Modulated Poisson Process (MMPP) has been extensively studied in random process theory and widely applied in various applications involving Poisson arrivals whose rate varies following a Markov process. Despite the rich literature on MMPP, very little is known on its intricate temporal dependence structure. No exact solution is available so far to capture the functional temporal dependence of MMPP at the stationary state over slotted times. This article tackles the above challenges with copula analysis. It not only presents a novel analytical framework to capture the temporal dependence of MMPP but also provides the exact copula-based solutions for single MMPP as well as the aggregate of independent MMPP. This theoretical contribution discloses functional dependence structure of MMPP. It also lays the foundation for many applications that rely on the temporal dependence of MMPP for adaptive control or predictive resource provisioning. We demonstrate case studies, with real-world trace data as well as simulation, to illustrate the practical significance of our analytical results.", acknowledgement = ack-nhfb, articleno = "14", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Ferragut:2017:CVC, author = "Andres Ferragut and Fernando Paganini and Adam Wierman", title = "Controlling the Variability of Capacity Allocations Using Service Deferrals", journal = j-TOMPECS, volume = "2", number = "3", pages = "15:1--15:??", month = sep, year = "2017", CODEN = "????", DOI = "https://doi.org/10.1145/3086506", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:14 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3086506", abstract = "Ensuring predictability is a crucial goal for service systems. Traditionally, research has focused on designing systems that ensure predictable performance for service requests. Motivated by applications in cloud computing and electricity markets, this article focuses on a different form of predictability: predictable allocations of service capacity. The focus of the article is a new model where service capacity can be scaled dynamically and service deferrals (subject to deadline constraints) can be used to control the variability of the active service capacity. Four natural policies for the joint problem of scheduling and managing the active service capacity are considered. For each, the variability of service capacity and the likelihood of deadline misses are derived. Further, the paper illustrates how pricing can be used to provide incentives for jobs to reveal deadlines and thus enable the possibility of service deferral in systems where the flexibility of jobs is not known to the system a priori.", acknowledgement = ack-nhfb, articleno = "15", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Li:2017:IPO, author = "Hao Li and Xinhai Xu and Miao Wang and Chao Li and Xiaoguang Ren and Xuejun Yang", title = "Insertion of {PETSc} in the {OpenFOAM} Framework", journal = j-TOMPECS, volume = "2", number = "3", pages = "16:1--16:??", month = sep, year = "2017", CODEN = "????", DOI = "https://doi.org/10.1145/3098821", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:14 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3098821", abstract = "OpenFOAM is a widely used open source framework for simulation in several areas of computational fluid dynamics and engineering. As a partial differential equation (PDE)-based framework, OpenFOAM suffers from a performance bottleneck in solving large-scale sparse linear systems of equations. To address the problem, this article proposes a novel OpenFOAM-PETSc framework by inserting PETSc, a dedicated numerical solving package, into the OpenFOAM to speed up the process of solving linear equation systems. The design of the OpenFOAM-PETSc framework is described, and the implementation of an efficient matrix conversion algorithm is given as a case study. Validation tests on a high-performance computing cluster show that OpenFOAM-PETSc reduces the time of solving PDEs by about 27\% in the lid-driven cavity flow case and by more than 50\% in flow around the cylinder case in comparison with OpenFOAM, without compromising the scalability. In addition, this article also gives a preliminary performance analysis of different numerical solution methods, which may provide guidelines for further optimizations.", acknowledgement = ack-nhfb, articleno = "16", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Liu:2017:FPE, author = "Yanpei Liu and Guilherme Cox and Qingyuan Deng and Stark C. Draper and Ricardo Bianchini", title = "Fast Power and Energy Management for Future Many-Core Systems", journal = j-TOMPECS, volume = "2", number = "3", pages = "17:1--17:??", month = sep, year = "2017", CODEN = "????", DOI = "https://doi.org/10.1145/3086504", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:14 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3086504", abstract = "Future servers will incorporate many active low-power modes for each core and for the main memory subsystem. Though these modes provide flexibility for power and/or energy management via Dynamic Voltage and Frequency Scaling (DVFS), prior work has shown that they must be managed in a coordinated manner. This requirement creates a combinatorial space of possible power mode configurations. As a result, it becomes increasingly challenging to quickly select the configuration that optimizes for both performance and power/energy efficiency. In this article, we propose a novel queuing model for working with the abundant active low-power modes in many-core systems. Based on the queuing model, we derive two fast algorithms that optimize for performance and efficiency using both CPU and memory DVFS. Our first algorithm, called FastCap, maximizes the performance of applications under a full-system power cap, while promoting fairness across applications. Our second algorithm, called FastEnergy, maximizes the full-system energy savings under predefined application performance loss bounds. Both FastCap and FastEnergy operate online and efficiently, using a small set of performance counters as input. To evaluate them, we simulate both algorithms for a many-core server running different types of workloads. Our results show that FastCap achieves better application performance and fairness than prior power capping techniques for the same power budget, whereas FastEnergy conserves more energy than prior energy management techniques for the same performance constraint. FastCap and FastEnergy together demonstrate the applicability of the queuing model for managing the abundant active low-power modes in many-core systems.", acknowledgement = ack-nhfb, articleno = "17", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Anselmi:2017:EC, author = "Jonatha Anselmi and Danilo Ardagna and John C. S. Lui and Adam Wierman and Yunjian Xu and Zichao Yang", title = "The Economics of the Cloud", journal = j-TOMPECS, volume = "2", number = "4", pages = "18:1--18:??", month = dec, year = "2017", CODEN = "????", DOI = "https://doi.org/10.1145/3086574", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:15 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3086574", abstract = "This article proposes a model to study the interaction of price competition and congestion in the cloud computing marketplace. Specifically, we propose a three-tier market model that captures a marketplace with users purchasing services from Software-as-a-Service (SaaS) providers, which in turn purchase computing resources from either Provider-as-a-Service (PaaS) or Infrastructure-as-a-Service (IaaS) providers. Within each level, we define and characterize market equilibria. Further, we use these characterizations to understand the relative profitability of SaaSs and PaaSs/IaaSs and to understand the impact of price competition on the user experienced performance, that is, the ``price of anarchy'' of the cloud marketplace. Our results highlight that both of these depend fundamentally on the degree to which congestion results from shared or dedicated resources in the cloud.", acknowledgement = ack-nhfb, articleno = "18", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Niu:2017:RAS, author = "Di Niu and Hong Xu and Baochun Li", title = "Resource Auto-Scaling and Sparse Content Replication for Video Storage Systems", journal = j-TOMPECS, volume = "2", number = "4", pages = "19:1--19:??", month = dec, year = "2017", CODEN = "????", DOI = "https://doi.org/10.1145/3079045", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:15 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3079045", abstract = "Many video-on-demand (VoD) providers are relying on public cloud providers for video storage, access, and streaming services. In this article, we investigate how a VoD provider may make optimal bandwidth reservations from a cloud service provider to guarantee the streaming performance while paying for the bandwidth, storage, and transfer costs. We propose a predictive resource auto-scaling system that dynamically books the minimum amount of bandwidth resources from multiple servers in a cloud storage system to allow the VoD provider to match its short-term demand projections. We exploit the anti-correlation between the demands of different videos for statistical multiplexing to hedge the risk of under-provisioning. The optimal load direction from video channels to cloud servers without replication constraints is derived with provable performance. We further study the joint load direction and sparse content placement problem that aims to reduce bandwidth reservation cost under sparse content replication requirements. We propose several algorithms, and especially an iterative L 1 -norm penalized optimization procedure, to efficiently solve the problem while effectively limiting the video migration overhead. The proposed system is backed up by a demand predictor that forecasts the expectation, volatility, and correlation of the streaming traffic associated with different videos based on statistical learning. Extensive simulations are conducted to evaluate our proposed algorithms, driven by the real-world workload traces collected from a commercial VoD system.", acknowledgement = ack-nhfb, articleno = "19", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Alves:2017:BMI, author = "Renan C. A. Alves and C{\'\i}ntia B. Margi", title = "Behavioral Model of {IEEE 802.15.4} Beacon-Enabled Mode Based on Colored {Petri} Net", journal = j-TOMPECS, volume = "2", number = "4", pages = "20:1--20:??", month = dec, year = "2017", CODEN = "????", DOI = "https://doi.org/10.1145/3115389", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:15 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3115389", abstract = "The IEEE 802.15.4 standard is widely employed in power-constrained scenarios, such as Wireless Sensor Networks deployments. Therefore, modeling this standard is useful to predict network performance and fine-tune parameter settings. Previous work rely on determining all reachable network states, usually by a Markov chain, which is often complex and error prone. In contrast, we provide a novel behavioral approach to the IEEE 802.15.4 modeling, which covers the literature gap in assessing all metrics of interest, modeling asymmetric traffic condition and fully comprising the beacon-enabled mode. In addition, it is possible to test different values for the parameters of the standard, such as aMaxFrameRetries, macMaxCSMABackoffs, initialCW, and aUnitBackoffPeriod. The model was validated by NS2 simulations and by a testbed composed of telosB motes.", acknowledgement = ack-nhfb, articleno = "20", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Neglia:2017:ATA, author = "Giovanni Neglia and Damiano Carra and Mingdong Feng and Vaishnav Janardhan and Pietro Michiardi and Dimitra Tsigkari", title = "Access-Time-Aware Cache Algorithms", journal = j-TOMPECS, volume = "2", number = "4", pages = "21:1--21:??", month = dec, year = "2017", CODEN = "????", DOI = "https://doi.org/10.1145/3149001", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:15 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3149001", abstract = "Most of the caching algorithms are oblivious to requests' timescale, but caching systems are capacity constrained and, in practical cases, the hit rate may be limited by the cache's impossibility to serve requests fast enough. In particular, the hard-disk access time can be the key factor capping cache performance. In this article, we present a new cache replacement policy that takes advantage of a hierarchical caching architecture, and in particular of access-time difference between memory and disk. Our policy is optimal when requests follow the independent reference model and significantly reduces the hard-disk load, as shown also by our realistic, trace-driven evaluation. Moreover, we show that our policy can be considered in a more general context, since it can be easily adapted to minimize any retrieval cost, as far as costs add over cache misses.", acknowledgement = ack-nhfb, articleno = "21", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Biondi:2017:WYL, author = "Elisabetta Biondi and Chiara Boldrini and Andrea Passarella and Marco Conti", title = "What You Lose When You Snooze: How Duty Cycling Impacts on the Contact Process in Opportunistic Networks", journal = j-TOMPECS, volume = "2", number = "4", pages = "22:1--22:??", month = dec, year = "2017", CODEN = "????", DOI = "https://doi.org/10.1145/3149007", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:15 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3149007", abstract = "In opportunistic networks, putting devices in energy-saving mode is crucial to preserve their battery, and hence to increase the lifetime of the network and foster user participation. A popular strategy for energy saving is duty cycling. However, when in energy-saving mode, users cannot communicate with each other. The side effects of duty cycling are twofold. On the one hand, duty cycling may reduce the number of usable contacts for delivering messages, increasing intercontact times, and delays. On the other hand, duty cycling may break long contacts into smaller contacts, thus also reducing the capacity of the opportunistic network. Despite the potential serious effects, the role played by duty cycling in opportunistic networks has been often neglected in the literature. In order to fill this gap, in this article, we propose a general model for deriving the pairwise contact and intercontact times measured when a duty cycling policy is superimposed on the original encounter process determined only by node mobility. The model we propose is general, i.e., not bound to a specific distribution of contact and intercontact times, and very accurate, as we show exploiting two traces of real human mobility for validation. Using this model, we derive several interesting results about the properties of measured contact and intercontact times with duty cycling: their distribution, how their coefficient of variation changes depending on the duty cycle value, and how the duty cycling affects the capacity and delay of an opportunistic network. The applicability of these results is broad, ranging from performance models for opportunistic networks that factor in the duty cycling effect, to the optimisation of the duty cycle to meet a certain target performance.", acknowledgement = ack-nhfb, articleno = "22", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Abouzeid:2017:LR, author = "Alhussein Abouzeid", title = "List of Reviewers", journal = j-TOMPECS, volume = "2", number = "4", pages = "23:1--23:??", month = dec, year = "2017", CODEN = "????", DOI = "https://doi.org/10.1145/3162084", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:15 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3162084", acknowledgement = ack-nhfb, articleno = "23", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Liu:2018:BGB, author = "Chubo Liu and Kenli Li and Zhuo Tang and Keqin Li", title = "Bargaining Game-Based Scheduling for Performance Guarantees in Cloud Computing", journal = j-TOMPECS, volume = "3", number = "1", pages = "1:1--1:??", month = feb, year = "2018", CODEN = "????", DOI = "https://doi.org/10.1145/3141233", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:15 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3141233", abstract = "In this article, we focus on request scheduling with performance guarantees of all users in cloud computing. Each cloud user submits requests with average response time requirement, and the cloud provider tries to find a scheduling scheme, i.e., allocating user requests to limited servers, such that the average response times of all cloud users can be guaranteed. We formulate the considered scenario into a cooperative game among multiple users and try to find a Nash bargaining solution (NBS), which can simultaneously satisfy all users' performance demands. We first prove the existence of NBS and then analyze its computation. Specifically, for the situation when all allocating substreams are strictly positive, we propose a computational algorithm ( CA ), which can find the NBS very efficiently. For the more general case, we propose an iterative algorithm ( IA ), which is based on duality theory. The convergence of our proposed IA algorithm is also analyzed. Finally, we conduct some numerical calculations. The experimental results show that our IA algorithm can find an appropriate scheduling strategy and converges to a stable state very quickly.", acknowledgement = ack-nhfb, articleno = "1", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Nordio:2018:STQ, author = "Alessandro Nordio and Alberto Tarable and Emilio Leonardi and Marco Ajmone Marsan", title = "Selecting the Top-Quality Item Through Crowd Scoring", journal = j-TOMPECS, volume = "3", number = "1", pages = "2:1--2:??", month = feb, year = "2018", CODEN = "????", DOI = "https://doi.org/10.1145/3157736", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:15 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3157736", abstract = "We investigate crowdsourcing algorithms for finding the top-quality item within a large collection of objects with unknown intrinsic quality values. This is an important problem with many relevant applications, such as in networked recommendation systems. The core of the algorithms is that objects are distributed to crowd workers, who return a noisy and biased evaluation. All received evaluations are then combined to identify the top-quality object. We first present a simple probabilistic model for the system under investigation. Then we devise and study a class of efficient adaptive algorithms to assign in an effective way objects to workers. We compare the performance of several algorithms, which correspond to different choices of the design parameters/metrics. In the simulations, we show that some of the algorithms achieve near optimal performance for a suitable setting of the system parameters.", acknowledgement = ack-nhfb, articleno = "2", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Li:2018:MFA, author = "Bin Li and Aditya Ramamoorthy and R. Srikant", title = "Mean-Field Analysis of Coding Versus Replication in Large Data Storage Systems", journal = j-TOMPECS, volume = "3", number = "1", pages = "3:1--3:??", month = feb, year = "2018", CODEN = "????", DOI = "https://doi.org/10.1145/3159172", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:15 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3159172", abstract = "We study cloud storage systems with a very large number of files stored in a very large number of servers. In such systems, files are either replicated or coded to ensure reliability, i.e., to guarantee file recovery from server failures. This redundancy in storage can further be exploited to improve system performance (mean file-access delay) through appropriate load-balancing (routing) schemes. However, it is unclear whether coding or replication is better from a system performance perspective since the corresponding queueing analysis of such systems is, in general, quite difficult except for the trivial case when the system load asymptotically tends to zero. Here, we study the more difficult case where the system load is not asymptotically zero. Using the fact that the system size is large, we obtain a mean-field limit for the steady-state distribution of the number of file access requests waiting at each server. We then use the mean-field limit to show that, for a given storage capacity per file, coding strictly outperforms replication at all traffic loads while improving reliability. Further, the factor by which the performance improves in the heavy traffic is at least as large as in the light-traffic case. Finally, we validate these results through extensive simulations.", acknowledgement = ack-nhfb, articleno = "3", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Chu:2018:EQC, author = "Cing-Yu Chu and Shannon Chen and Yu-Chuan Yen and Su-Ling Yeh and Hao-Hua Chu and Polly Huang", title = "{EQ}: A {QoE}-Centric Rate Control Mechanism for {VoIP} Calls", journal = j-TOMPECS, volume = "3", number = "1", pages = "4:1--4:??", month = feb, year = "2018", CODEN = "????", DOI = "https://doi.org/10.1145/3170430", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:15 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3170430", abstract = "The rising popularity of data calls and the slowed global economy have posed a challenge to voice data networking-how to satisfy the growing user demand for VoIP calls under limited network resources. In a bandwidth-constrained network in particular, raising the bitrate for one call implies a lowered bitrate for another. Therefore, knowing whether it is worthwhile to raise one call's bitrate while other users might complain is crucial to the design of a user-centric rate control mechanism. To this end, previous work (Chen et al. 2012) has reported a log-like relationship between bitrate and user experience (i.e., QoE) in Skype calls. To show that the relationship extends to more general VoIP calls, we conduct a 60-participant user study via the Amazon Mechanical Turk crowdsourcing platform and reaffirm the log-like relationship between the call bitrate and user experience in widely used AMR-WB. The relationship gives rise to a simple and practical rate control scheme that exponentially quantizes the steps of rate change, therefore the name-exponential quantization (EQ). To support that EQ is effective in addressing the challenge, we show through a formal analysis that the resulting bandwidth allocation is optimal in both the overall QoE and the number of calls served. To relate EQ to existing rate control mechanisms, we show in a simulation study that the bitrates of calls administered by EQ converge over time and outperform those controlled by a (na{\"\i}ve) greedy mechanism and the mechanism implemented in Skype.", acknowledgement = ack-nhfb, articleno = "4", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Zhou:2018:OED, author = "Ruiting Zhou and Zongpeng Li and Chuan Wu", title = "An Online Emergency Demand Response Mechanism for Cloud Computing", journal = j-TOMPECS, volume = "3", number = "1", pages = "5:1--5:??", month = feb, year = "2018", CODEN = "????", DOI = "https://doi.org/10.1145/3177755", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:15 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3177755", abstract = "This article studies emergency demand response (EDR) mechanisms from a data center perspective, where a cloud participates in a mandatory EDR program while receiving computing job bids from cloud users in an online fashion. We target a realistic EDR mechanism where (i) the cloud provider dynamically packs different types of resources on servers into requested VMs and computes job schedules to meet users' requirements, (ii) the power consumption of servers in the cloud is limited by the grid through the EDR program, and (iii) the operation cost of the cloud is considered in the calculation of social welfare, measured by an electricity cost that consists of both volume charge and peak charge. We propose an online auction for dynamic cloud resource provisioning that is under the control of the EDR program, runs in polynomial time, achieves truthfulness, and close-to-optimal social welfare for the cloud ecosystem. In the design of the online auction, we first propose a new framework, compact exponential LPs, to handle job scheduling constraints in the time domain. We then develop a posted pricing auction framework toward the truthful online auction design, which leverages the classic primal-dual technique for approximation algorithm design. We evaluate our online auctions through both theoretical analysis and empirical studies driven by real-world traces.", acknowledgement = ack-nhfb, articleno = "5", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Koziolek:2018:SIS, author = "Anne Koziolek and Evgenia Smirni", title = "Special Issue: Selected Paper From the {8th {ACM\slash SPEC} International Conference on Performance Engineering (ICPE 2017)}", journal = j-TOMPECS, volume = "3", number = "2", pages = "6:1--6:??", month = apr, year = "2018", CODEN = "????", DOI = "https://doi.org/10.1145/3186329", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:16 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3186329", acknowledgement = ack-nhfb, articleno = "6e", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Wang:2018:EAA, author = "Cheng Wang and Qianlin Liang and Bhuvan Urgaonkar", title = "An Empirical Analysis of {Amazon EC2} Spot Instance Features Affecting Cost-Effective Resource Procurement", journal = j-TOMPECS, volume = "3", number = "2", pages = "6:1--6:??", month = apr, year = "2018", CODEN = "????", DOI = "https://doi.org/10.1145/3164538", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:16 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3164538", abstract = "Many cost-conscious public cloud workloads (``tenants'') are turning to Amazon EC2's spot instances because, on average, these instances offer significantly lower prices (up to 10 times lower) than on-demand and reserved instances of comparable advertised resource capacities. To use spot instances effectively, a tenant must carefully weigh the lower costs of these instances against their poorer availability. Toward this, we empirically study four features of EC2 spot instance operation that a cost-conscious tenant may find useful to model. Using extensive evaluation based on historical spot instance data, we show shortcomings in the state-of-the-art modeling of these features that we overcome. As an extension to our prior work, we conduct data analysis on a rich dataset of the latest spot price traces collected from a variety of EC2 spot markets. Our analysis reveals many novel properties of spot instance operation, some of which offer predictive value whereas others do not. Using these insights, we design predictors for our features that offer a balance between computational efficiency (allowing for online resource procurement) and cost efficacy. We explore ``case studies'' wherein we implement prototypes of dynamic spot instance procurement advised by our predictors for two types of workloads. Compared to the state of the art, our approach achieves (i) comparable cost but much better performance (fewer bid failures) for a latency-sensitive in-memory Memcached cache and (ii) an additional 18\% cost savings with comparable (if not better than) performance for a delay-tolerant batch workload.", acknowledgement = ack-nhfb, articleno = "6", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Cassell:2018:DPM, author = "Benjamin Cassell and Tyler Szepesi and Jim Summers and Tim Brecht and Derek Eager and Bernard Wong", title = "Disk Prefetching Mechanisms for Increasing {HTTP} Streaming Video Server Throughput", journal = j-TOMPECS, volume = "3", number = "2", pages = "7:1--7:??", month = apr, year = "2018", CODEN = "????", DOI = "https://doi.org/10.1145/3164536", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:16 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3164536", abstract = "Most video streaming traffic is delivered over HTTP using standard web servers. While traditional web server workloads consist of requests that are primarily for small files that can be serviced from the file system cache, HTTP video streaming workloads often service a long tail of large infrequently requested videos. As a result, optimizing disk accesses is critical to obtaining good server throughput. In this article we explore serialized, aggressive disk prefetching, a technique that can be used to improve the throughput of HTTP streaming video web servers. We identify how serialization and aggressive prefetching affect performance, and, based on our findings, we construct and evaluate Libception, an application-level shim library that implements both techniques. By dynamically linking against Libception at runtime, applications are able to transparently obtain benefits from serialization and aggressive prefetching without needing to change their source code. In contrast to other approaches that modify applications, make kernel changes, or attempt to optimize kernel tuning, Libception provides a portable and relatively simple system in which techniques for optimizing I/O in HTTP video streaming servers can be implemented and evaluated. We empirically evaluate the efficacy of serialization and aggressive prefetching both with and without Libception, using three web servers (Apache, nginx, and the userver) running on two operating systems (FreeBSD and Linux). We find that, by using Libception, we can improve streaming throughput for all three web servers by at least a factor of 2 on FreeBSD and a factor of 2.5 on Linux. Additionally, we find that with significant tuning of Linux kernel parameters, we can achieve similar performance to Libception by globally modifying Linux's disk prefetch behaviour. Finally, we demonstrate Libception's ability to reduce the completion time of a microbenchmark involving two applications competing for disk resources.", acknowledgement = ack-nhfb, articleno = "7", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Ilyushkin:2018:EPE, author = "Alexey Ilyushkin and Ahmed Ali-Eldin and Nikolas Herbst and Andr{\'e} Bauer and Alessandro V. Papadopoulos and Dick Epema and Alexandru Iosup", title = "An Experimental Performance Evaluation of Autoscalers for Complex Workflows", journal = j-TOMPECS, volume = "3", number = "2", pages = "8:1--8:??", month = apr, year = "2018", CODEN = "????", DOI = "https://doi.org/10.1145/3164537", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:16 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3164537", abstract = "Elasticity is one of the main features of cloud computing allowing customers to scale their resources based on the workload. Many autoscalers have been proposed in the past decade to decide on behalf of cloud customers when and how to provision resources to a cloud application based on the workload utilizing cloud elasticity features. However, in prior work, when a new policy is proposed, it is seldom compared to the state-of-the-art, and is often compared only to static provisioning using a predefined quality of service target. This reduces the ability of cloud customers and of cloud operators to choose and deploy an autoscaling policy, as there is seldom enough analysis on the performance of the autoscalers in different operating conditions and with different applications. In our work, we conduct an experimental performance evaluation of autoscaling policies, using as application model workflows, a popular formalism for automating resource management for applications with well-defined yet complex structures. We present a detailed comparative study of general state-of-the-art autoscaling policies, along with two new workflow-specific policies. To understand the performance differences between the seven policies, we conduct various experiments and compare their performance in both pairwise and group comparisons. We report both individual and aggregated metrics. As many workflows have deadline requirements on the tasks, we study the effect of autoscaling on workflow deadlines. Additionally, we look into the effect of autoscaling on the accounted and hourly based charged costs, and we evaluate performance variability caused by the autoscaler selection for each group of workflow sizes. Our results highlight the trade-offs between the suggested policies, how they can impact meeting the deadlines, and how they perform in different operating conditions, thus enabling a better understanding of the current state-of-the-art.", acknowledgement = ack-nhfb, articleno = "8", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Khan:2018:RAE, author = "Kashif Nizam Khan and Mikael Hirki and Tapio Niemi and Jukka K. Nurminen and Zhonghong Ou", title = "{RAPL} in Action: Experiences in Using {RAPL} for Power Measurements", journal = j-TOMPECS, volume = "3", number = "2", pages = "9:1--9:??", month = apr, year = "2018", CODEN = "????", DOI = "https://doi.org/10.1145/3177754", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:16 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3177754", abstract = "To improve energy efficiency and comply with the power budgets, it is important to be able to measure the power consumption of cloud computing servers. Intel's Running Average Power Limit (RAPL) interface is a powerful tool for this purpose. RAPL provides power limiting features and accurate energy readings for CPUs and DRAM, which are easily accessible through different interfaces on large distributed computing systems. Since its introduction, RAPL has been used extensively in power measurement and modeling. However, the advantages and disadvantages of RAPL have not been well investigated yet. To fill this gap, we conduct a series of experiments to disclose the underlying strengths and weaknesses of the RAPL interface by using both customized microbenchmarks and three well-known application level benchmarks: Stream, Stress-ng, and ParFullCMS. Moreover, to make the analysis as realistic as possible, we leverage two production-level power measurement datasets from the Taito, a supercomputing cluster of the Finnish Center of Scientific Computing and also replicate our experiments on Amazon EC2. Our results illustrate different aspects of RAPL and document the findings through comprehensive analysis. Our observations reveal that RAPL readings are highly correlated with plug power, promisingly accurate enough, and have negligible performance overhead. Experimental results suggest RAPL can be a very useful tool to measure and monitor the energy consumption of servers without deploying any complex power meters. We also show that there are still some open issues, such as driver support, non-atomicity of register updates, and unpredictable timings that might weaken the usability of RAPL in certain scenarios. For such scenarios, we pinpoint solutions and workarounds.", acknowledgement = ack-nhfb, articleno = "9", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Du:2018:EOL, author = "Yuhuan Du and Gustavo {De Veciana}", title = "Efficiency and Optimality of Largest Deficit First Prioritization: Dynamic User Prioritization for Soft Real-Time Applications", journal = j-TOMPECS, volume = "3", number = "3", pages = "10:1--10:??", month = aug, year = "2018", CODEN = "????", DOI = "https://doi.org/10.1145/3200479", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:16 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3200479", abstract = "An increasing number of real-time applications with compute and/or communication deadlines are being supported on a shared infrastructure. Such applications can often tolerate occasional deadline violations without substantially impacting their Quality of Service (QoS). This article explores the efficient allocation of shared resources to satisfy such QoS requirements. We study a simple framework which decouples this problem into two subproblems: (1) dynamic prioritization of users based on arbitrary functions of their deficits (difference of achieved vs. required QoS), and (2) priority-based resource allocation on the underlying compute fabric. In this article, we shall assume the solution to the latter is fixed, e.g., as realized in the task prioritization capabilities of current hardware/software, and focus on compatible solutions to the former. We first characterize the set of feasible QoS requirements and show the optimality of max weight-like prioritization. We then consider simple weighted Largest Deficit First (w-LDF) prioritization policies, where users with higher weighted QoS deficits are given higher priority. The article gives an inner bound for the feasible set under w-LDF policies, and, under an additional monotonicity assumption, characterizes its geometry leading to a sufficient condition for optimality. Additional insights on the efficiency ratio of w-LDF policies, the optimality of hierarchical-LDF, and characterization of clustering of failures are also discussed.", acknowledgement = ack-nhfb, articleno = "10", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Chen:2018:CEO, author = "Shutong Chen and Zhi Zhou and Fangming Liu and Zongpeng Li and Shaolei Ren", title = "{CloudHeat}: An Efficient Online Market Mechanism for Datacenter Heat Harvesting", journal = j-TOMPECS, volume = "3", number = "3", pages = "11:1--11:??", month = aug, year = "2018", CODEN = "????", DOI = "https://doi.org/10.1145/3199675", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:16 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3199675", abstract = "Datacenters are major energy consumers and dissipate an enormous amount of waste heat. Simple outdoor discharging of datacenter heat is energy-consuming and environmentally unfriendly. By harvesting datacenter waste heat and selling to the district heating system (DHS), both energy cost compensation and environment protection can be achieved. To realize such benefits in practice, an efficient market mechanism is required to incentivize the participation of datacenters. This work proposes CloudHeat, an online reverse auction mechanism for the DHS to solicit heat bids from datacenters. To minimize long-term social operational cost of the DHS and the datacenters, we apply a RFHC approach for decomposing the long-term problem into a series of one-round auctions, guaranteeing a small loss in competitive ratio. The one-round optimization is still NP-hard, and we employ a randomized auction framework to simultaneously guarantee truthfulness, polynomial running time, and an approximation ratio of 2. The performance of CloudHeat is validated through theoretical analysis and trace-driven simulation studies.", acknowledgement = ack-nhfb, articleno = "11", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Varki:2018:GGP, author = "Elizabeth Varki", title = "{GPSonflow}: Geographic Positioning of Storage for Optimal Nice Flow", journal = j-TOMPECS, volume = "3", number = "3", pages = "12:1--12:??", month = aug, year = "2018", CODEN = "????", DOI = "https://doi.org/10.1145/3197656", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:16 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3197656", abstract = "This article evaluates the maximum data flow from a sender to a receiver via the internet when all transmissions are scheduled for early morning hours. The significance of early morning hours is that internet congestion is low while users sleep. When the sender and receiver lie in proximal time zones, a direct transmission from sender to receiver can be scheduled for early morning hours. When the sender and receiver are separated by several time zones such that their sleep times are non-overlapping, data can still be transmitted during early morning hours with an indirect store-and-forward transfer. The data are transmitted from the sender to intermediate end networks or data centers that serve as storage hops en route to receiver. The storage hops are placed in zones that are time proximal to the sender or the receiver so that all transmissions to and from storage hops occur during low-congestion early morning hours. This article finds the optimal locations and bandwidth distributions of storage hops for maximum nice internet flow from a sender to a receiver.", acknowledgement = ack-nhfb, articleno = "12", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Ray:2018:SSC, author = "Avik Ray and Sujay Sanghavi and Sanjay Shakkottai", title = "Searching for a Single Community in a Graph", journal = j-TOMPECS, volume = "3", number = "3", pages = "13:1--13:??", month = aug, year = "2018", CODEN = "????", DOI = "https://doi.org/10.1145/3200863", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:16 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3200863", abstract = "In standard graph clustering/community detection, one is interested in partitioning the graph into more densely connected subsets of nodes. In contrast, the search problem of this article aims to only find the nodes in a single such community, the target, out of the many communities that may exist. To do so, we are given suitable side information about the target; for example, a very small number of nodes from the target are labeled as such. We consider a general yet simple notion of side information: all nodes are assumed to have random weights, with nodes in the target having higher weights on average. Given these weights and the graph, we develop a variant of the method of moments that identifies nodes in the target more reliably, and with lower computation, than generic community detection methods that do not use side information and partition the entire graph. Our empirical results show significant gains in runtime, and also gains in accuracy over other graph clustering algorithms.", acknowledgement = ack-nhfb, articleno = "13", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Malik:2018:SAL, author = "Maria Malik and Setareh Rafatirad and Houman Homayoun", title = "System and Architecture Level Characterization of Big Data Applications on Big and Little Core Server Architectures", journal = j-TOMPECS, volume = "3", number = "3", pages = "14:1--14:??", month = aug, year = "2018", CODEN = "????", DOI = "https://doi.org/10.1145/3229049", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:16 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3229049", abstract = "The rapid growth in data yields challenges to process data efficiently using current high-performance server architectures such as big Xeon cores. Furthermore, physical design constraints, such as power and density, have become the dominant limiting factor for scaling out servers. Low-power embedded cores in servers such as little Atom have emerged as a promising solution to enhance energy-efficiency to address these challenges. Therefore, the question of whether to process the big data applications on big Xeon- or Little Atom-based servers becomes important. In this work, through methodical investigation of power and performance measurements, and comprehensive application-level, system-level, and micro-architectural level analysis, we characterize dominant big data applications on big Xeon- and little Atom-based server architectures. The characterization results across a wide range of real-world big data applications, and various software stacks demonstrate how the choice of big- versus little-core-based server for energy-efficiency is significantly influenced by the size of data, performance constraints, and presence of accelerator. In addition, we analyze processor resource utilization of this important class of applications,such as memory footprints, CPU utilization, and disk bandwidth, to understand their run-time behavior. Furthermore, we perform micro-architecture-level analysis to highlight where improvement is needed in big- and little-core microarchitectures to address their performance bottlenecks.", acknowledgement = ack-nhfb, articleno = "14", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Li:2018:MFG, author = "Jian Li and Bainan Xia and Xinbo Geng and Hao Ming and Srinivas Shakkottai and Vijay Subramanian and Le Xie", title = "Mean Field Games in Nudge Systems for Societal Networks", journal = j-TOMPECS, volume = "3", number = "4", pages = "15:1--15:??", month = sep, year = "2018", CODEN = "????", DOI = "https://doi.org/10.1145/3232076", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:16 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3232076", abstract = "We consider the general problem of resource sharing in societal networks, consisting of interconnected communication, transportation, energy, and other networks important to the functioning of society. Participants in such network need to take decisions daily, both on the quantity of resources to use as well as the periods of usage. With this in mind, we discuss the problem of incentivizing users to behave in such a way that society as a whole benefits. To perceive societal level impact, such incentives may take the form of rewarding users with lottery tickets based on good behavior and periodically conducting a lottery to translate these tickets into real rewards. We will pose the user decision problem as a mean field game and the incentives question as one of trying to select a good mean field equilibrium (MFE). In such a framework, each agent (a participant in the societal network) takes a decision based on an assumed distribution of actions of his/her competitors and the incentives provided by the social planner. The system is said to be at MFE if the agent's action is a sample drawn from the assumed distribution. We will show the existence of such an MFE under general settings, and also illustrate how to choose an attractive equilibrium using as an example demand-response in the (smart) electricity network.", acknowledgement = ack-nhfb, articleno = "15", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Pajevic:2018:EPC, author = "Ljubica Pajevic and Viktoria Fodor and Gunnar Karlsson", title = "Ensuring Persistent Content in Opportunistic Networks via Stochastic Stability Analysis", journal = j-TOMPECS, volume = "3", number = "4", pages = "16:1--16:??", month = sep, year = "2018", CODEN = "????", DOI = "https://doi.org/10.1145/3232161", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:16 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3232161", abstract = "The emerging device-to-device communication solutions and the abundance of mobile applications and services make opportunistic networking not only a feasible solution but also an important component of future wireless networks. Specifically, the distribution of locally relevant content could be based on the community of mobile users visiting an area, if long-term content survival can be ensured this way. In this article, we establish the conditions of content survival in such opportunistic networks, considering the user mobility patterns, as well as the time users keep forwarding the content, as the controllable system parameter. We model the content spreading with an epidemic process, and derive a stochastic differential equations based approximation. By means of stability analysis, we determine the necessary user contribution to ensure content survival. We show that the required contribution from the users depends significantly on the size of the population, that users need to redistribute content only in a short period within their stay, and that they can decrease their contribution significantly in crowded areas. Hence, with the appropriate control of the system parameters, opportunistic content sharing can be both reliable and sustainable.", acknowledgement = ack-nhfb, articleno = "16", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Wang:2018:QMS, author = "Weikun Wang and Giuliano Casale and Ajay Kattepur and Manoj K. Nambiar", title = "{QMLE}: A Methodology for Statistical Inference of Service Demands from Queueing Data", journal = j-TOMPECS, volume = "3", number = "4", pages = "17:1--17:??", month = sep, year = "2018", CODEN = "????", DOI = "https://doi.org/10.1145/3233180", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:16 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3233180", abstract = "Estimating the demands placed by services on physical resources is an essential step for the definition of performance models. For example, scalability analysis relies on these parameters to predict queueing delays under increasing loads. In this article, we investigate maximum likelihood (ML) estimators for demands at load-independent and load-dependent resources in systems with parallelism constraints. We define a likelihood function based on state measurements and derive necessary conditions for its maximization. We then obtain novel estimators that accurately and inexpensively obtain service demands using only aggregate state data. With our approach, and also thanks to approximation methods for computing marginal and joint distributions for the load-dependent case, confidence intervals can be rigorously derived, explicitly taking into account both topology and concurrency levels of the services. Our estimators and their confidence intervals are validated against simulations and real system measurements for two multi-tier applications, showing high accuracy also in models with load-dependent resources.", acknowledgement = ack-nhfb, articleno = "17", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Azimi:2018:SVS, author = "Reza Azimi and Tyler Fox and Wendy Gonzalez and Sherief Reda", title = "Scale-Out vs Scale-Up: A Study of {ARM}-based {SoCs} on Server-Class Workloads", journal = j-TOMPECS, volume = "3", number = "4", pages = "18:1--18:??", month = sep, year = "2018", CODEN = "????", DOI = "https://doi.org/10.1145/3232162", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:16 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/pvm.bib; http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3232162", abstract = "ARM 64-bit processing has generated enthusiasm to develop ARM-based servers that are targeted for both data centers and supercomputers. In addition to the server-class components and hardware advancements, the ARM software environment has grown substantially over the past decade. Major development ecosystems and libraries have been ported and optimized to run on ARM, making ARM suitable for server-class workloads. There are two trends in available ARM SoCs: mobile-class ARM SoCs that rely on the heterogeneous integration of a mix of CPU cores, GPGPU streaming multiprocessors (SMs), and other accelerators, and the server-class SoCs that instead rely on integrating a larger number of CPU cores with no GPGPU support and a number of IO accelerators. For scaling the number of processing cores, there are two different paradigms: mobile-class SoCs that use scale-out architecture in the form of a cluster of simpler systems connected over a network, and server-class ARM SoCs that use the scale-up solution and leverage symmetric multiprocessing to pack a large number of cores on the chip. In this article, we present ScaleSoC cluster, which is a scale-out solution based on mobile class ARM SoCs. ScaleSoC leverages fast network connectivity and GPGPU acceleration to improve performance and energy efficiency compared to previous ARM scale-out clusters. We consider a wide range of modern server-class parallel workloads to study both scaling paradigms, including latency-sensitive transactional workloads, MPI-based CPU and GPGPU-accelerated scientific applications, and emerging artificial intelligence workloads. We study the performance and energy efficiency of ScaleSoC compared to server-class ARM SoCs and discrete GPGPUs in depth. We quantify the network overhead on the performance of ScaleSoC and show that packing a large number of ARM cores on a single chip does not necessarily guarantee better performance, due to the fact that shared resources, such as last-level cache, become performance bottlenecks. We characterize the GPGPU accelerated workloads and demonstrate that for applications that can leverage the better CPU-GPGPU balance of the ScaleSoC cluster, performance and energy efficiency improve compared to discrete GPGPUs.", acknowledgement = ack-nhfb, articleno = "18", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Herbst:2018:QCP, author = "Nikolas Herbst and Andr{\'e} Bauer and Samuel Kounev and Giorgos Oikonomou and Erwin {Van Eyk} and George Kousiouris and Athanasia Evangelinou and Rouven Krebs and Tim Brecht and Cristina L. Abad and Alexandru Iosup", title = "Quantifying Cloud Performance and Dependability: Taxonomy, Metric Design, and Emerging Challenges", journal = j-TOMPECS, volume = "3", number = "4", pages = "19:1--19:??", month = sep, year = "2018", CODEN = "????", DOI = "https://doi.org/10.1145/3236332", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:16 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3236332", abstract = "In only a decade, cloud computing has emerged from a pursuit for a service-driven information and communication technology (ICT), becoming a significant fraction of the ICT market. Responding to the growth of the market, many alternative cloud services and their underlying systems are currently vying for the attention of cloud users and providers. To make informed choices between competing cloud service providers, permit the cost-benefit analysis of cloud-based systems, and enable system DevOps to evaluate and tune the performance of these complex ecosystems, appropriate performance metrics, benchmarks, tools, and methodologies are necessary. This requires re-examining old system properties and considering new system properties, possibly leading to the re-design of classic benchmarking metrics such as expressing performance as throughput and latency (response time). In this work, we address these requirements by focusing on four system properties: (i) elasticity of the cloud service, to accommodate large variations in the amount of service requested, (ii){\~ }performance isolation between the tenants of shared cloud systems and resulting performance variability, (iii){\~ }availability of cloud services and systems, and (iv) the operational risk of running a production system in a cloud environment. Focusing on key metrics for each of these properties, we review the state-of-the-art, then select or propose new metrics together with measurement approaches. We see the presented metrics as a foundation toward upcoming, future industry-standard cloud benchmarks.", acknowledgement = ack-nhfb, articleno = "19", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Jiang:2018:CTA, author = "Bo Jiang and Philippe Nain and Don Towsley", title = "On the Convergence of the {TTL} Approximation for an {LRU} Cache under Independent Stationary Request Processes", journal = j-TOMPECS, volume = "3", number = "4", pages = "20:1--20:??", month = sep, year = "2018", CODEN = "????", DOI = "https://doi.org/10.1145/3239164", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:16 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3239164", abstract = "The modeling and analysis of an LRU cache is extremely challenging as exact results for the main performance metrics (e.g., hit rate) are either lacking or cannot be used because of their high computational complexity for large caches. As a result, various approximations have been proposed. The state-of-the-art method is the so-called TTL approximation, first proposed and shown to be asymptotically exact for IRM requests by Fagin [13]. It has been applied to various other workload models and numerically demonstrated to be accurate but without theoretical justification. In this article, we provide theoretical justification for the approximation in the case where distinct contents are described by independent stationary and ergodic processes. We show that this approximation is exact as the cache size and the number of contents go to infinity. This extends earlier results for the independent reference model. Moreover, we establish results not only for the aggregate cache hit probability but also for every individual content. Last, we obtain bounds on the rate of convergence.", acknowledgement = ack-nhfb, articleno = "20", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Abid:2018:LR, author = "Amine Abid", title = "List of Reviewers", journal = j-TOMPECS, volume = "3", number = "4", pages = "21:1--21:??", month = sep, year = "2018", CODEN = "????", DOI = "https://doi.org/10.1145/3271430", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:16 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3271430", acknowledgement = ack-nhfb, articleno = "21", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Yin:2019:ETL, author = "Ping Yin and Sen Yang and Jun Xu and Jim Dai and Bill Lin", title = "Efficient Traffic Load-Balancing via Incremental Expansion of Routing Choices", journal = j-TOMPECS, volume = "4", number = "1", pages = "1:1--1:??", month = mar, year = "2019", CODEN = "????", DOI = "https://doi.org/10.1145/3243173", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:17 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3243173", abstract = "Routing policies play a major role in the performance of communication networks. Backpressure-based adaptive routing algorithms where traffic is load balanced along different routing paths on a per-packet basis have been studied extensively in the literature. Although backpressure-based algorithms have been shown to be networkwide throughput optimal, they typically have poor delay performance under light or moderate loads, because packets may be sent over unnecessarily long routes. Further, backpressure-based algorithms have required every node to compute differential backlogs for every per-destination queue with the corresponding per-destination queue at every adjacent node, which is expensive given the large number of possible pairwise differential backlogs between neighbor nodes. In this article, we propose new backpressure-based adaptive routing algorithms that only use shortest-path routes to destinations when they are sufficient to accommodate the given traffic load, but the proposed algorithms will incrementally expand routing choices as needed to accommodate increasing traffic loads. We show analytically by means of fluid analysis that the proposed algorithms retain networkwide throughput optimality, and we show empirically by means of simulations that our proposed algorithms provide substantial improvements in delay performance. Our evaluations further show that, in practice, our approach dramatically reduces the number of pairwise differential backlogs that have to be computed and the amount of corresponding backlog information that has to be exchanged, because routing choices are only incrementally expanded as needed.", acknowledgement = ack-nhfb, articleno = "1", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Chen:2019:EQA, author = "Hao Chen and Yijia Zhang and Michael C. Caramanis and Ayse K. Coskun", title = "{EnergyQARE}: {QoS}-Aware Data Center Participation in Smart Grid Regulation Service Reserve Provision", journal = j-TOMPECS, volume = "4", number = "1", pages = "2:1--2:??", month = mar, year = "2019", CODEN = "????", DOI = "https://doi.org/10.1145/3243172", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:17 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3243172", abstract = "Power market operators have recently introduced smart grid demand response (DR), in which electricity consumers regulate their power usage following market requirements. DR helps stabilize the grid and enables integrating a larger amount of intermittent renewable power generation. Data centers provide unique opportunities for DR participation due to their flexibility in both workload servicing and power consumption. While prior studies have focused on data center participation in legacy DR programs such as dynamic energy pricing and peak shaving, this article studies data centers in emerging DR programs, i.e., demand side capacity reserves. Among different types of capacity reserves, regulation service reserves (RSRs) are especially attractive due to their relatively higher value. This article proposes EnergyQARE, the Energy and Quality-of-Service (QoS) Aware R SR Enabler, an approach that enables data center RSR provision in real-life scenarios. EnergyQARE not only provides a bidding strategy in RSR provision, but also contains a runtime policy that adaptively modulates data center power through server power management and server provisioning based on workload QoS feedback. To reflect real-life scenarios, this runtime policy handles a heterogeneous set of jobs and considers transition time delay of servers. Simulated numerical results demonstrate that in a general data center scenario, EnergyQARE provides close to 50\% of data center average power consumption as reserves to the market and saves up to 44\% in data center electricity cost, while still meeting workload QoS constraints. Case studies in this article show that the percentages of savings are not sensitive to a specific type of non-interactive workload, or the size of the data center, although they depend strongly on data center utilization and parameters of server power states.", acknowledgement = ack-nhfb, articleno = "2", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Li:2019:QCS, author = "Zhenhua Li and Yongfeng Zhang and Yunhao Liu and Tianyin Xu and Ennan Zhai and Yao Liu and Xiaobo Ma and Zhenyu Li", title = "A Quantitative and Comparative Study of Network-Level Efficiency for Cloud Storage Services", journal = j-TOMPECS, volume = "4", number = "1", pages = "3:1--3:??", month = mar, year = "2019", CODEN = "????", DOI = "https://doi.org/10.1145/3274526", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:17 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3274526", abstract = "Cloud storage services such as Dropbox and OneDrive provide users with a convenient and reliable way to store and share data from anywhere, on any device, and at any time. Their cornerstone is the data synchronization (sync) operation, which automatically maps the changes in users' local file systems to the cloud via a series of network communications in a timely manner. Without careful design and implementation, however, the data sync mechanisms could generate overwhelming traffic, causing tremendous financial overhead and performance penalties to both service providers and end users. This article addresses a simple yet critical question: Is the current data sync traffic of cloud storage services efficiently used? We first define a novel metric TUE to quantify the Traffic Usage Efficiency of data synchronization. Then, by conducting comprehensive benchmark experiments and reverse engineering the data sync processes of eight widely used cloud storage services, we uncover their manifold practical endeavors for optimizing the TUE, including three intra-file approaches (compression, incremental sync, and interrupted transfer resumption), two cross-file/-user approaches ( i.e., deduplication and peer-assisted offloading), two batching approaches (file bundling and sync deferment), and two web-specific approaches (thumbnail views and dynamic content loading). Our measurement results reveal that a considerable portion of the data sync traffic is, in a sense, wasteful and can be effectively avoided or significantly reduced via carefully designed data sync mechanisms. Most importantly, our study not only offers practical, actionable guidance for providers to build more efficient, traffic-economic services, but also helps end users pick appropriate services that best fit their use cases and budgets.", acknowledgement = ack-nhfb, articleno = "3", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Gupta:2019:ERS, author = "Samarth Gupta and Sharayu Moharir", title = "Effect of Recommendations on Serving Content with Unknown Demand", journal = j-TOMPECS, volume = "4", number = "1", pages = "4:1--4:??", month = mar, year = "2019", CODEN = "????", DOI = "https://doi.org/10.1145/3289324", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:17 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3289324", abstract = "We consider the task of content replication in distributed content delivery systems used by Video-on-Demand (VoD) services with large content catalogs. The prior work in this area focuses on the setting where each request is generated independent of all past requests. Motivated by the fact that most popular VoD services offer recommendations to users based on their viewing history, in a departure from existing studies, we study the setting with time-correlation in requests coming from each user. We use a Markovian process to model each user's request process. In addition to introducing time-correlation in user requests, our model is consistent with empirically observed properties of the request process for VoD services with recommendation engines. In the setting where the underlying Markov Chain is unknown and has to be learned from the very requests the system is trying to serve, we show that separating the task of estimating content popularity and using the estimates to design a static content replication policy is strictly sub-optimal. To prove this, we show that an adaptive policy, which jointly performs the task of estimation and content replication, outperforms all policies that separate the task of estimation and content replication.", acknowledgement = ack-nhfb, articleno = "4", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Harrison:2019:MRT, author = "P. G. Harrison and N. M. Patel and J. F. P{\'e}rez and Z. Qiu", title = "Managing Response Time Tails by Sharding", journal = j-TOMPECS, volume = "4", number = "1", pages = "5:1--5:??", month = mar, year = "2019", CODEN = "????", DOI = "https://doi.org/10.1145/3300143", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:17 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3300143", abstract = "Matrix analytic methods are developed to compute the probability distribution of response times (i.e., data access times) in distributed storage systems protected by erasure coding, which is implemented by sharding a data object into N fragments, only K \N of which are required to reconstruct the object. This leads to a partial-fork-join model with a choice of canceling policies for the redundant N - K tasks. The accuracy of the analytical model is supported by tests against simulation in a broad range of setups. At increasing workload intensities, numerical results show the extent to which increasing the redundancy level reduces the mean response time of storage reads and significantly flattens the tail of their distribution; this is demonstrated at medium-high quantiles, up to the 99th. The quantitative reduction in response time achieved by two policies for canceling redundant tasks is also shown: for cancel-at-finish and cancel-at-start, which limits the additional load introduced whilst losing the benefit of selectivity amongst fragment service times.", acknowledgement = ack-nhfb, articleno = "5", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{KhudaBukhsh:2019:PPE, author = "Wasiur R. KhudaBukhsh and Sounak Kar and Amr Rizk and Heinz Koeppl", title = "Provisioning and Performance Evaluation of Parallel Systems with Output Synchronization", journal = j-TOMPECS, volume = "4", number = "1", pages = "6:1--6:??", month = mar, year = "2019", CODEN = "????", DOI = "https://doi.org/10.1145/3300142", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:17 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3300142", abstract = "Parallel server frameworks are widely deployed in modern large-data processing applications. Intuitively, splitting and parallel processing of the workload provides accelerated application response times and scaling flexibility. Examples of such frameworks include MapReduce, Hadoop, and Spark. For many applications, the dynamics of such systems are naturally captured by a Fork-Join (FJ) queuing model, where incoming jobs are split into tasks each of which is mapped to exactly one server. When all the tasks that belong to one job are executed, the job is reassembled and leaves the system. We consider this behavior at the output as a synchronization constraint. In this article, we study the performance of such parallel systems for different server properties, e.g., work-conservingness, phase-type behavior, and as suggested by recent evidence, for bursty input job arrivals. We establish a Large Deviations Principle for the steady-state job waiting times in an FJ system based on Markov-additive processes. Building on that, we present a performance analysis framework for FJ systems and provide computable bounds on the tail probabilities of the steady-state waiting times. We validate our bounds using estimates obtained through simulations. In addition, we define and analyze provisioning, a flexible division of jobs into tasks, in FJ systems. Finally, we use this framework together with real-world traces to show the benefits of an adaptive provisioning system that adjusts the service within an FJ system based on the arrival intensity.", acknowledgement = ack-nhfb, articleno = "6", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Wang:2019:ESR, author = "Da Wang and Gauri Joshi and Gregory W. Wornell", title = "Efficient Straggler Replication in Large-Scale Parallel Computing", journal = j-TOMPECS, volume = "4", number = "2", pages = "7:1--7:??", month = jun, year = "2019", CODEN = "????", DOI = "https://doi.org/10.1145/3310336", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:17 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3310336", abstract = "In a cloud computing job with many parallel tasks, the tasks on the slowest machines (straggling tasks) become the bottleneck in the job completion. Computing frameworks such as MapReduce and Spark tackle this by replicating the straggling tasks and waiting for any one copy to finish. Despite being adopted in practice, there is little analysis of how replication affects the latency and the cost of additional computing resources. In this article, we provide a framework to analyze this latency-cost tradeoff and find the best replication strategy by answering design questions, such as (1) when to replicate straggling tasks, (2) how many replicas to launch, and (3) whether to kill the original copy or not. Our analysis reveals that for certain execution time distributions, a small amount of task replication can drastically reduce both latency and the cost of computing resources. We also propose an algorithm to estimate the latency and cost based on the empirical distribution of task execution time. Evaluations using samples in the Google Cluster Trace suggest further latency and cost reduction compared to the existing replication strategy used in MapReduce.", acknowledgement = ack-nhfb, articleno = "7", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Izadpanah:2019:PAP, author = "Ramin Izadpanah and Benjamin A. Allan and Damian Dechev and Jim Brandt", title = "Production Application Performance Data Streaming for System Monitoring", journal = j-TOMPECS, volume = "4", number = "2", pages = "8:1--8:??", month = jun, year = "2019", CODEN = "????", DOI = "https://doi.org/10.1145/3319498", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:17 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/pvm.bib; http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3319498", abstract = "In this article, we present an approach to streaming collection of application performance data. Practical application performance tuning and troubleshooting in production high-performance computing (HPC) environments requires an understanding of how applications interact with the platform, including (but not limited to) parallel programming libraries such as Message Passing Interface (MPI). Several profiling and tracing tools exist that collect heavy runtime data traces either in memory (released only at application exit) or on a file system (imposing an I/O load that may interfere with the performance being measured). Although these approaches are beneficial in development stages and post-run analysis, a systemwide and low-overhead method is required to monitor deployed applications continuously. This method must be able to collect information at both the application and system levels to yield a complete performance picture. In our approach, an application profiler collects application event counters. A sampler uses an efficient inter-process communication method to periodically extract the application counters and stream them into an infrastructure for performance data collection. We implement a tool-set based on our approach and integrate it with the Lightweight Distributed Metric Service (LDMS) system, a monitoring system used on large-scale computational platforms. LDMS provides the infrastructure to create and gather streams of performance data in a low overhead manner. We demonstrate our approach using applications implemented with MPI, as it is one of the most common standards for the development of large-scale scientific applications. We utilize our tool-set to study the impact of our approach on an open source HPC application, Nalu. Our tool-set enables us to efficiently identify patterns in the behavior of the application without source-level knowledge. We leverage LDMS to collect system-level performance data and explore the correlation between the system and application events. Also, we demonstrate how our tool-set can help detect anomalies with a low latency. We run tests on two different architectures: a system enabled with Intel Xeon Phi and another system equipped with Intel Xeon processor. Our overhead study shows our method imposes at most 0.5\% CPU usage overhead on the application in realistic deployment scenarios.", acknowledgement = ack-nhfb, articleno = "8", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Hellemans:2019:PRD, author = "Tim Hellemans and Benny {Van Houdt}", title = "Performance of Redundancy($d$) with Identical\slash Independent Replicas", journal = j-TOMPECS, volume = "4", number = "2", pages = "9:1--9:??", month = jun, year = "2019", CODEN = "????", DOI = "https://doi.org/10.1145/3316768", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:17 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3316768", abstract = "Queueing systems with redundancy have received considerable attention recently. The idea of redundancy is to reduce latency by replicating each incoming job a number of times and to assign these replicas to a set of randomly selected servers. As soon as one replica completes service the remaining replicas are cancelled. Most prior work on queueing systems with redundancy assumes that the job durations of the different replicas are independent and identically distributed (i.i.d.), which yields insights that can be misleading for computer system design. In this article, we develop a differential equation, using the cavity method, to assess the workload and response time distribution in a large homogeneous system with redundancy without the need to rely on this independence assumption. More specifically, we assume that the duration of each replica of a single job is identical across the servers and follows a general service time distribution. Simulation results suggest that the differential equation yields exact results as the system size tends to infinity and can be used to study the stability of the system. We also compare our system to the one with i.i.d. replicas and show the similarity in the analysis used for independent, respectively, identical replicas.", acknowledgement = ack-nhfb, articleno = "9", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Wang:2019:OTA, author = "Qingyang Wang and Shungeng Zhang and Yasuhiko Kanemasa and Calton Pu and Balaji Palanisamy and Lilian Harada and Motoyuki Kawaba", title = "Optimizing {$N$}-Tier Application Scalability in the Cloud: A Study of Soft Resource Allocation", journal = j-TOMPECS, volume = "4", number = "2", pages = "10:1--10:??", month = jun, year = "2019", CODEN = "????", DOI = "https://doi.org/10.1145/3326120", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:17 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/java2010.bib; http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3326120", abstract = "An effective cloud computing environment requires both good performance and high efficiency of computing resources. Through extensive experiments using a representative n-tier benchmark application (Rice University Bulletin Board System (RUBBoS)), we show that the soft resource allocation (e.g., thread pool size and database connection pool size) in component servers has a significant impact on the overall system performance, especially at high system utilization scenarios. Concretely, the same software resource allocation can be a good setting in one hardware configuration and then becomes an either under- or over-allocation in a slightly different hardware configuration, causing a significant performance drop. We have also observed some interesting phenomena that were caused by the non-trivial dependencies between the soft resources of servers in different tiers. For instance, the thread pool size in an Apache web server can limit the total number of concurrent requests to the downstream servers, which surprisingly decreases the Central Processing Unit (CPU) utilization of the Clustered Java Database Connectivity (C-JDBC) clustering middleware as the workload increases. To provide a globally optimal (or near-optimal) soft resource allocation of each tier in the system, we propose a practical iterative solution approach by combining a soft resource aware queuing network model and the fine-grained measurement data of every component server. Our results show that to truly scale complex distributed systems such as n-tier web applications with expected performance in the cloud, we need to carefully manage soft resource allocation in the system.", acknowledgement = ack-nhfb, articleno = "10", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Namazi:2019:SSO, author = "Alireza Namazi and Saeed Safari and Siamak Mohammadi and Meisam Abdollahi", title = "{SORT}: Semi Online Reliable Task Mapping for Embedded Multi-Core Systems", journal = j-TOMPECS, volume = "4", number = "2", pages = "11:1--11:??", month = jun, year = "2019", CODEN = "????", DOI = "https://doi.org/10.1145/3322899", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:17 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3322899", abstract = "This article proposes a Semi Online Reliable Task (SORT) mapping approach to many-core platforms divided into two sections: offline and online. The offline section is a twofolded approach. It maintains the reliability of the mapped task graph against soft errors considering the reliability threshold defined by designers. As wear-out mechanisms decrease the lifetime of the system, our proposed approach increases the lifetime of the system using task migration scenarios. It specifies task migration plans with the minimum overhead using a novel heuristic approach. SORT maintains the required level of reliability of the task graph in the whole lifetime of the system using a replication technique with minimum replica overhead, maximum achievable performance, and minimum temperature increase. The online segment uses migration plans obtained in the offline segment to increase the lifetime and also permanently maintains the reliability threshold for the task graph during runtime. Results show that the effectiveness of SORT improves on bigger mesh sizes and higher reliability thresholds. Simulation results obtained from real benchmarks show that the proposed approach decreases design-time calculation up to 4,371\% compared to exhaustive exploration while achieving a lifetime negligibly lower than the exhaustive solution (up to 5.83\%).", acknowledgement = ack-nhfb, articleno = "11", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Nguyen:2019:PFR, author = "T. T. Hang Nguyen and Olivier Brun and Balakrishna J. Prabhu", title = "Performance of a Fixed Reward Incentive Scheme for Two-hop {DTNs} with Competing Relays", journal = j-TOMPECS, volume = "4", number = "2", pages = "12:1--12:??", month = jun, year = "2019", CODEN = "????", DOI = "https://doi.org/10.1145/3325288", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:17 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3325288", abstract = "We analyze the performance of an incentive scheme for two-hop Delay-Tolerant Networks (DTNs) in which a backlogged source proposes a fixed reward to the relays to deliver a message. Only one message at a time is proposed by the source. For a given message, only the first relay to deliver it gets the reward corresponding to this message thereby inducing a competition between the relays. The relays seek to maximize the expected reward for each message, whereas the objective of the source is to satisfy a given constraint on the probability of message delivery. We show that the optimal policy of a relay is of threshold type: it accepts a message until a first threshold and then keeps the message until it either meets the destination or reaches the second threshold. Formulas for computing the thresholds as well as probability of message delivery are derived for a backlogged source.", acknowledgement = ack-nhfb, articleno = "12", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Verschoren:2019:EDC, author = "Robin Verschoren and Benny {Van Houdt}", title = "On the Endurance of the $d$-Choices Garbage Collection Algorithm for Flash-Based {SSDs}", journal = j-TOMPECS, volume = "4", number = "3", pages = "13:1--13:??", month = sep, year = "2019", CODEN = "????", DOI = "https://doi.org/10.1145/3326121", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:17 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3326121", abstract = "Garbage collection (GC) algorithms for flash-based solid-state drives (SSDs) have a profound impact on its performance and many studies have focused on assessing the so-called write amplification of various GC algorithms. In this article, we consider the family of d -choices GC algorithms and study (a) the extent in which these algorithms induce unequal wear and (b) the manner in which they affect the lifetime of the drive. For this purpose, we introduce two performance measures: PE fairness and SSD endurance. We study the impact of the d -choices GC algorithm on both these measures under different workloads (uniform, synthetic and trace-based) when combined with two different write modes. Numerical results show that the more complex of the two write modes, which requires hot/cold data identification, may not necessarily give rise to a significantly better SSD endurance. Further, the d -choices GC algorithm is often shown to strike a good balance between garbage collection and wear leveling for small d values (e.g., d = 10), yielding high endurance.", acknowledgement = ack-nhfb, articleno = "13", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Phan:2019:NFE, author = "Tien-Dat Phan and Guillaume Pallez and Shadi Ibrahim and Padma Raghavan", title = "A New Framework for Evaluating Straggler Detection Mechanisms in {MapReduce}", journal = j-TOMPECS, volume = "4", number = "3", pages = "14:1--14:??", month = sep, year = "2019", CODEN = "????", DOI = "https://doi.org/10.1145/3328740", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:17 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3328740", abstract = "Big Data systems (e.g., Google MapReduce, Apache Hadoop, Apache Spark) rely increasingly on speculative execution to mask slow tasks, also known as stragglers, because a job's execution time is dominated by the slowest task instance. Big Data systems typically identify stragglers and speculatively run copies of those tasks with the expectation that a copy may complete faster to shorten job execution times. There is a rich body of recent results on straggler mitigation in MapReduce. However, the majority of these do not consider the problem of accurately detecting stragglers. Instead, they adopt a particular straggler detection approach and then study its effectiveness in terms of performance, e.g., reduction in job completion time or higher efficiency, e.g., high resource utilization. In this article, we consider a complete framework for straggler detection and mitigation. We start with a set of metrics that can be used to characterize and detect stragglers including Precision, Recall, Detection Latency, Undetected Time, and Fake Positive. We then develop an architectural model by which these metrics can be linked to measures of performance including execution time and system energy overheads. We further conduct a series of experiments to demonstrate which metrics and approaches are more effective in detecting stragglers and are also predictive of effectiveness in terms of performance and energy efficiencies. For example, our results indicate that the default Hadoop straggler detector could be made more effective. In a certain case, Precision is low and only 55\% of those detected are actual stragglers and the Recall, i.e., percent of actual detected stragglers, is also relatively low at 56\%. For the same case, the hierarchical approach (i.e., a green-driven detector based on the default one) achieves a Precision of 99\% and a Recall of 29\%. This increase in Precision can be translated to achieve lower execution time and energy consumption, and thus higher performance and energy efficiency; compared to the default Hadoop mechanism, the energy consumption is reduced by almost 31\%. These results demonstrate how our framework can offer useful insights and be applied in practical settings to characterize and design new straggler detection mechanisms for MapReduce systems.", acknowledgement = ack-nhfb, articleno = "14", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Lim:2019:PCI, author = "Chiun Lin Lim and Ki Suh Lee and Han Wang and Hakim Weatherspoon and Ao Tang", title = "Packet Clustering Introduced by Routers: Modeling, Analysis, and Experiments", journal = j-TOMPECS, volume = "4", number = "3", pages = "15:1--15:??", month = sep, year = "2019", CODEN = "????", DOI = "https://doi.org/10.1145/3345032", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:17 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3345032", abstract = "In this article, we investigate a router's inherent variation on packet processing time and its effect on interpacket delay and packet clustering. We propose a simple pipeline model incorporating the inherent variation, and two metrics-one to measure packet clustering and one to quantify inherent variation. To isolate the effect of the inherent variation, we begin our analysis with no cross traffic and step through setups where the input streams have different data rates, packet size, and go through a different number of hops. We show that a homogeneous input stream with a sufficiently large interpacket gap will emerge at the router's output with interpacket delays that are negative correlated with adjacent values and have symmetrical distributions. We show that for smaller interpacket gaps, the change in packet clustering is smaller. It is also shown that the degree of packet clustering could in fact decrease for a clustered input. We generalize our results by adding cross traffic. All the results predicted by the model are validated with experiments with real routers. We also investigated several factors that can affect the inherent variation as well as some potential applications of this study.", acknowledgement = ack-nhfb, articleno = "15", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Bakhshaliyev:2019:ICI, author = "Khalid Bakhshaliyev and Muhammed Abdullah Canbaz and Mehmet Hadi Gunes", title = "Investigating Characteristics of {Internet} Paths", journal = j-TOMPECS, volume = "4", number = "3", pages = "16:1--16:??", month = sep, year = "2019", CODEN = "????", DOI = "https://doi.org/10.1145/3342286", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:17 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3342286", abstract = "Interactive and multimedia applications depend on the stability of end-to-end paths for predictable performance and good quality of service. On the other hand, network providers depend on multiple paths to ensure fault tolerance and use load balancing between these paths to enhance the overall network throughput. In this study, we analyze path dynamics for both end-to-end paths and path segments within service providers' networks using 2 months of measurement data from the RIPE Atlas platform, which collects path traces between a fixed set of source and destination pairs every 15 minutes. We observe that 78\% of the end-to-end routes have at least two alternative Autonomous System (AS) paths with some end-to-end routes going through hundreds of different AS paths during the 2 months of analysis. While AS level paths are often prevalent for a day, there are considerable changes in the routing of the trace packets over the ASes for a longer duration of a month or longer. Analyzing end-to-end paths for routing anomalies, we observe that 4.4\% of the path traces (involving 18\% of the ASes) contain routing loops indicating misconfiguration of routers. Some of the ASes had over 100 routers involved in loops in path traces through their networks. We observe a much higher rate of anomalies in the AS level, with 45\% of path traces containing an AS loop. Additionally, we discovered that few of the ASes bounce-back packets where some traces through their network traverse routers in both forward and backward directions. Determining path segments belonging to each AS, we further explore ingress to egress paths of ASes in addition to the source to destination paths within the AS. Analyzing trace segments between ingresses and egresses of an AS, we realized more than half of the ASes have the same router level path between any ingress-egress pair for the 2 months, but others implement load balancing. These results are different from earlier studies that indicated a high level of path dynamism. Our results indicate that the end-to-end path dynamism is due to the Border Gateway Protocol level rather than the router level within ASes.", acknowledgement = ack-nhfb, articleno = "16", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Skevakis:2019:SOF, author = "Emmanouil Skevakis and Ioannis Lambadaris and Hassan Halabian", title = "Scheduling for Optimal File-Transfer Delay using Chunked Random Linear Network Coding Broadcast", journal = j-TOMPECS, volume = "4", number = "3", pages = "17:1--17:??", month = sep, year = "2019", CODEN = "????", DOI = "https://doi.org/10.1145/3340242", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:17 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3340242", abstract = "We study the broadcast transmission of a single file to an arbitrary number of receivers using Random Linear Network Coding (RLNC) in a network with unreliable channels. Due to the increased computational complexity of the decoding process (especially for large files), we apply chunked RLNC (i.e., RLNC is applied within non-overlapping subsets of the file). In our work, we show the optimality of the Least Received (LR) batch scheduling policy with regards to the expected file transfer completion time. The LR policy strives to keep the receiver queues balanced. This is done by transmitting packets (corresponding to encoded batches) that are needed by the receivers with the shortest queues of successfully received packets. Furthermore, we provide formulas for the expected time for the file transmission to all receivers using the LR batch scheduling policy and the minimum achievable coding window size in the case of a pre-defined delay constraint. Moreover, we evaluate through simulations a modification of the LR policy in a more realistic system setting with reduced feedback from the receivers. Finally, we provide an initial analysis and further modifications to the LR policy for time-correlated channels and asymmetric channels.", acknowledgement = ack-nhfb, articleno = "17", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Friedlander:2019:GLC, author = "Eric Friedlander and Vaneet Aggarwal", title = "Generalization of {LRU} Cache Replacement Policy with Applications to Video Streaming", journal = j-TOMPECS, volume = "4", number = "3", pages = "18:1--18:??", month = sep, year = "2019", CODEN = "????", DOI = "https://doi.org/10.1145/3345022", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sat Sep 21 07:21:17 MDT 2019", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/citation.cfm?id=3345022", abstract = "Caching plays a crucial role in networking systems to reduce the load on the network and is commonly employed by content delivery networks (CDNs) to improve performance. One of the commonly used mechanisms, Least Recently Used (LRU), works well for identical file sizes. However, for asymmetric file sizes, the performance deteriorates. This article proposes an adaptation to the LRU strategy, called gLRU, where the file is sub-divided into equal-sized chunks. In this strategy, a chunk of the newly requested file is added in the cache, and a chunk of the least-recently-used file is removed from the cache. Even though approximate analysis for the hit rate has been studied for LRU, the analysis does not extend to gLRU, since the metric of interest is no longer the hit rate as the cache has partial files. This article provides a novel approximation analysis for this policy where the cache may have partial file contents. The approximation approach is validated by simulations. Further, gLRU outperforms the LRU strategy for a Zipf file popularity distribution and censored Pareto file size distribution for the file download times. Video streaming applications can further use the partial cache contents to help the stall duration significantly, and the numerical results indicate significant improvements (32\%) in stall duration using the gLRU strategy as compared to the LRU strategy. Furthermore, the gLRU replacement policy compares favorably to two other cache replacement policies when simulated on MSR Cambridge Traces obtained from the SNIA IOTTA repository.", acknowledgement = ack-nhfb, articleno = "18", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "http://dl.acm.org/pub.cfm?id=J1525", } @Article{Kalbasi:2019:AAM, author = "Amir Kalbasi and Diwakar Krishnamurthy and Jerry Rolia", title = "{AMIR}: Analytic Method for Improving Responsiveness by Reducing Burstiness", journal = j-TOMPECS, volume = "4", number = "4", pages = "19:1--19:36", month = dec, year = "2019", CODEN = "????", DOI = "https://doi.org/10.1145/3365669", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Mar 19 13:56:10 MDT 2020", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/abs/10.1145/3365669", abstract = "Service demand burstiness, or serial correlations in resource service demands, has previously been shown to have an adverse impact on system performance metrics such as response time. This article proposes AMIR, an analytic framework to characterize \ldots{}", acknowledgement = ack-nhfb, articleno = "19", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Wu:2019:FAS, author = "Xiaohu Wu and Francesco {De Pellegrini} and Guanyu Gao and Giuliano Casale", title = "A Framework for Allocating Server Time to Spot and On-Demand Services in Cloud Computing", journal = j-TOMPECS, volume = "4", number = "4", pages = "20:1--20:31", month = dec, year = "2019", CODEN = "????", DOI = "https://doi.org/10.1145/3366682", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Mar 19 13:56:10 MDT 2020", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/abs/10.1145/3366682", abstract = "Cloud computing delivers value to users by facilitating their access to servers at any time period needed. An approach is to provide both on-demand and spot services on shared servers. The former allows users to access servers on demand at a fixed price \ldots{}", acknowledgement = ack-nhfb, articleno = "20", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Vial:2019:RCP, author = "Daniel Vial and Vijay Subramanian", title = "On the Role of Clustering in Personalized {PageRank} Estimation", journal = j-TOMPECS, volume = "4", number = "4", pages = "21:1--21:33", month = dec, year = "2019", CODEN = "????", DOI = "https://doi.org/10.1145/3366635", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Mar 19 13:56:10 MDT 2020", bibsource = "http://www.math.utah.edu/pub/tex/bib/pagerank.bib; http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/abs/10.1145/3366635", abstract = "Personalized PageRank (PPR) is a measure of the importance of a node from the perspective of another (we call these nodes the target and the source, respectively). PPR has been used in many applications, such as offering a Twitter user (the source) recommendations of whom to follow (targets deemed important by PPR); additionally, PPR has been used in graph-theoretic problems such as community detection. However, computing PPR is infeasible for large networks like Twitter, so efficient estimation algorithms are necessary.\par In this work, we analyze the relationship between PPR estimation complexity and clustering. First, we devise algorithms to estimate PPR for many source/target pairs. In particular, we propose an enhanced version of the existing single pair estimator Bidirectional-PPR that is more useful as a primitive for many pair estimation. We then show that the common underlying graph can be leveraged to efficiently and jointly estimate PPR for many pairs rather than treating each pair separately using the primitive algorithm. Next, we show the complexity of our joint estimation scheme relates closely to the degree of clustering among the sources and targets at hand, indicating that estimating PPR for many pairs is easier when clustering occurs. Finally, we consider estimating PPR when several machines are available for parallel computation, devising a method that leverages our clustering findings, specifically the quantities computed in situ, to assign tasks to machines in a manner that reduces computation time. This demonstrates that the relationship between complexity and clustering has important consequences in a practical distributed setting.", acknowledgement = ack-nhfb, articleno = "21", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Wang:2019:CSC, author = "Xiaoming Wang and Di Xiao and Xiaoyong Li and Daren B. H. Cline and Dmitri Loguinov", title = "Consistent Sampling of Churn Under Periodic Non-Stationary Arrivals in Distributed Systems", journal = j-TOMPECS, volume = "4", number = "4", pages = "22:1--22:33", month = dec, year = "2019", CODEN = "????", DOI = "https://doi.org/10.1145/3368510", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Mar 19 13:56:10 MDT 2020", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/abs/10.1145/3368510", abstract = "Characterizing user churn has become an important research area of networks and distributed systems, both in theoretical analysis and system design. A realistic churn model, often measured using periodic observation, should replicate two key properties \ldots{}", acknowledgement = ack-nhfb, articleno = "22", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Borst:2019:LR, author = "Sem Borst and Carey Williamson", title = "List of Reviewers", journal = j-TOMPECS, volume = "4", number = "4", pages = "23:1--23:2", month = dec, year = "2019", CODEN = "????", DOI = "https://doi.org/10.1145/3369841", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Mar 19 13:56:10 MDT 2020", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/abs/10.1145/3369841", acknowledgement = ack-nhfb, articleno = "23", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Mciver:2020:ISS, author = "Annabelle Mciver and Andr{\'a}s Horv{\'a}th", title = "Introduction to the Special Section on Quantitative Evaluation of Systems {(QEST 2018)}", journal = j-TOMPECS, volume = "5", number = "1", pages = "1:1--1:1", month = feb, year = "2020", CODEN = "????", DOI = "https://doi.org/10.1145/3376999", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Mar 19 13:56:11 MDT 2020", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/abs/10.1145/3376999", acknowledgement = ack-nhfb, articleno = "1", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Salamati:2020:LAT, author = "Mahmoud Salamati and Sadegh Soudjani and Rupak Majumdar", title = "A {Lyapunov} Approach for Time-Bounded Reachability of {CTMCs} and {CTMDPs}", journal = j-TOMPECS, volume = "5", number = "1", pages = "2:1--2:29", month = feb, year = "2020", CODEN = "????", DOI = "https://doi.org/10.1145/3371923", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Mar 19 13:56:11 MDT 2020", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/abs/10.1145/3371923", abstract = "Time-bounded reachability is a fundamental problem in model checking continuous-time Markov chains (CTMCs) and Markov decision processes (CTMDPs) for specifications in continuous stochastic logics. It can be computed by numerically solving a \ldots{}", acknowledgement = ack-nhfb, articleno = "2", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Marin:2020:DRA, author = "Andrea Marin and Sabina Rossi and Matteo Sottana", title = "Dynamic Resource Allocation in Fork--Join Queues", journal = j-TOMPECS, volume = "5", number = "1", pages = "3:1--3:28", month = feb, year = "2020", CODEN = "????", DOI = "https://doi.org/10.1145/3372376", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Mar 19 13:56:11 MDT 2020", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/abs/10.1145/3372376", abstract = "Fork--join systems play a pivotal role in the analysis of distributed systems, telecommunication infrastructures, and storage systems. In this article, we consider a fork-join system consisting of $K$ parallel servers, each of which works on one \ldots{}", acknowledgement = ack-nhfb, articleno = "3", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Yang:2020:EPC, author = "Jinfeng Yang and Bingzhe Li and David J. Lilja", title = "Exploring Performance Characteristics of the {Optane $3$D Xpoint} Storage Technology", journal = j-TOMPECS, volume = "5", number = "1", pages = "4:1--4:28", month = feb, year = "2020", CODEN = "????", DOI = "https://doi.org/10.1145/3372783", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Mar 19 13:56:11 MDT 2020", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/abs/10.1145/3372783", abstract = "Intel's Optane solid-state nonvolatile storage device is constructed using their new 3D Xpoint technology. Although it is claimed that this technology can deliver substantial performance improvements compared to NAND-based storage systems, its performance characteristics have not been well studied. In this study, intensive experiments and measurements have been carried out to extract the intrinsic performance characteristics of the Optane SSD, including the basic I/O performance behavior, advanced interleaving technology, performance consistency under a highly intensive I/O workload, influence of unaligned request size, elimination of write-driven garbage collection, read disturb issues, and tail latency problem. The performance is compared to that of a conventional NAND SSD to indicate the performance difference of the Optane SSD in each scenario. In addition, by using TPC-H, a read-intensive benchmark, a database system's performance has been studied on our target storage devices to quantify the potential benefits of the Optane SSD to a real application. Finally, the performance impact of hybrid Optane and NAND SSD storage systems on a database application has been investigated.", acknowledgement = ack-nhfb, articleno = "4", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Rattaro:2020:QPD, author = "Claudina Rattaro and Laura Aspirot and Ernesto Mordecki and Pablo Belzarena", title = "{QoS} Provision in a Dynamic Channel Allocation Based on Admission Control Decisions", journal = j-TOMPECS, volume = "5", number = "1", pages = "5:1--5:29", month = feb, year = "2020", CODEN = "????", DOI = "https://doi.org/10.1145/3372786", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Mar 19 13:56:11 MDT 2020", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/abs/10.1145/3372786", abstract = "Cognitive Radio Networks have emerged in the last decades as a solution of two problems: spectrum underutilization and spectrum scarcity. In this work, we propose a dynamic spectrum sharing mechanism, where primary users have strict priority over \ldots{}", acknowledgement = ack-nhfb, articleno = "5", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Jiang:2020:LHS, author = "Qingye Jiang and Young Choon Lee and Albert Y. Zomaya", title = "The Limit of Horizontal Scaling in Public Clouds", journal = j-TOMPECS, volume = "5", number = "1", pages = "6:1--6:22", month = feb, year = "2020", CODEN = "????", DOI = "https://doi.org/10.1145/3373356", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Thu Mar 19 13:56:11 MDT 2020", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/abs/10.1145/3373356", abstract = "Public cloud users are educated to practice horizontal scaling at the application level, with the assumption that more processing capacity can be achieved by adding nodes into the server fleet. In reality, however, applications --- even those specifically \ldots{}", acknowledgement = ack-nhfb, articleno = "6", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Awad:2020:IAD, author = "Mahmoud Awad and Daniel A. Menasc{\'e}", title = "{iModel}: Automatic Derivation of Analytic Performance Models", journal = j-TOMPECS, volume = "5", number = "2", pages = "7:1--7:30", month = apr, year = "2020", CODEN = "????", DOI = "https://doi.org/10.1145/3374220", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sun Mar 28 07:27:06 MDT 2021", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3374220", abstract = "Deriving analytic performance models requires detailed knowledge of the architecture and behavior of the computer system being modeled as well as modeling skills. This detailed knowledge may not be readily available (or it may be impractical to gather) \ldots{}", acknowledgement = ack-nhfb, articleno = "7", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Vassio:2020:UIO, author = "Luca Vassio and Michele Garetto and Carla Chiasserini and Emilio Leonardi", title = "User Interaction with Online Advertisements: Temporal Modeling and Optimization of Ads Placement", journal = j-TOMPECS, volume = "5", number = "2", pages = "8:1--8:26", month = apr, year = "2020", CODEN = "????", DOI = "https://doi.org/10.1145/3377144", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sun Mar 28 07:27:06 MDT 2021", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3377144", abstract = "We consider an online advertisement system and focus on the impact of user interaction and response to targeted advertising campaigns. We analytically model the system dynamics accounting for the user behavior and devise strategies to maximize a \ldots{}", acknowledgement = ack-nhfb, articleno = "8", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Plakia:2020:SSS, author = "Maria Plakia and Evripides Tzamousis and Thomais Asvestopoulou and Giorgos Pantermakis and Nick Filippakis and Henning Schulzrinne and Yana Kane-Esrig and Maria Papadopouli", title = "Should {I} Stay or Should {I} Go: Analysis of the Impact of Application {QoS} on User Engagement in {YouTube}", journal = j-TOMPECS, volume = "5", number = "2", pages = "9:1--9:32", month = apr, year = "2020", CODEN = "????", DOI = "https://doi.org/10.1145/3377873", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sun Mar 28 07:27:06 MDT 2021", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3377873", abstract = "To improve the user engagement, especially under moderate to high traffic demand, it is important to understand the impact of the network and application QoS on user experience. This article comparatively evaluates the impact of impairments, with \ldots{}", acknowledgement = ack-nhfb, articleno = "9", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Gupta:2020:SPD, author = "Manu K. Gupta and N. Hemachandra and J. Venkateswaran", title = "Some Parameterized Dynamic Priority Policies for Two-Class {M/G/1} Queues: Completeness and Applications", journal = j-TOMPECS, volume = "5", number = "2", pages = "10:1--10:37", month = apr, year = "2020", CODEN = "????", DOI = "https://doi.org/10.1145/3384390", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sun Mar 28 07:27:06 MDT 2021", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3384390", abstract = "Completeness of a dynamic priority scheduling scheme is of fundamental importance for the optimal control of queues in areas as diverse as computer communications, communication networks, supply/value chains, and manufacturing systems. Our first main \ldots{}", acknowledgement = ack-nhfb, articleno = "10", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Sieber:2020:SAU, author = "Christian Sieber and Susanna Schwarzmann and Andreas Blenk and Thomas Zinner and Wolfgang Kellerer", title = "Scalable Application- and User-aware Resource Allocation in Enterprise Networks Using End-Host Pacing", journal = j-TOMPECS, volume = "5", number = "3", pages = "11:1--11:41", month = nov, year = "2020", CODEN = "????", DOI = "https://doi.org/10.1145/3381996", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sun Mar 28 07:27:06 MDT 2021", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3381996", abstract = "Providing scalable user- and application-aware resource allocation for heterogeneous applications sharing an enterprise network is still an unresolved problem. The main challenges are as follows: (i) How do we define user- and application-aware shares \ldots{}", acknowledgement = ack-nhfb, articleno = "11", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Costa:2020:ENN, author = "Georges DA Costa and Jean-Marc Pierson and Leandro Fontoura-Cupertino", title = "Effectiveness of Neural Networks for Power Modeling for Cloud and {HPC}: It's Worth It!", journal = j-TOMPECS, volume = "5", number = "3", pages = "12:1--12:36", month = nov, year = "2020", CODEN = "????", DOI = "https://doi.org/10.1145/3388322", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sun Mar 28 07:27:06 MDT 2021", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3388322", abstract = "Power consumption of servers and applications are of utmost importance as computers are becoming ubiquitous, from smart phones to IoT and full-fledged computers. To optimize their power consumption, knowledge is necessary during execution at different \ldots{}", acknowledgement = ack-nhfb, articleno = "12", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Liao:2020:TEB, author = "Jianwei Liao and Zhibing Sha and Zhigang Cai and Zhiming Liu and Kenli Li and Wei-Keng Liao and Alok N. Choudhary and Yutaka Ishiakwa", title = "Toward Efficient Block Replication Management in Distributed Storage", journal = j-TOMPECS, volume = "5", number = "3", pages = "13:1--13:27", month = nov, year = "2020", CODEN = "????", DOI = "https://doi.org/10.1145/3412450", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sun Mar 28 07:27:06 MDT 2021", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3412450", abstract = "Distributed/parallel file systems commonly suffer from load imbalance and resource contention due to the bursty characteristic exhibited in scientific applications. This article presents an adaptive scheme supporting dynamic block data replication and \ldots{}", acknowledgement = ack-nhfb, articleno = "13", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Raeis:2020:AQM, author = "Majid Raeis and Almut Burchard and J{\"o}rg Liebeherr", title = "Analysis of a Queueing Model for Energy Storage Systems with Self-discharge", journal = j-TOMPECS, volume = "5", number = "3", pages = "14:1--14:26", month = nov, year = "2020", CODEN = "????", DOI = "https://doi.org/10.1145/3422711", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sun Mar 28 07:27:06 MDT 2021", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3422711", abstract = "This article presents an analysis of a recently proposed queueing system model for energy storage with discharge. Even without a load, energy storage systems experience a reduction of the stored energy through self-discharge. In some storage \ldots{}", acknowledgement = ack-nhfb, articleno = "14", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Golubchik:2021:MNE, author = "Leana Golubchik", title = "A Message from the New {Editor-in-Chief}", journal = j-TOMPECS, volume = "5", number = "4", pages = "15:1--15:1", month = mar, year = "2021", CODEN = "????", DOI = "https://doi.org/10.1145/3432597", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sun Mar 28 07:27:07 MDT 2021", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3432597", acknowledgement = ack-nhfb, articleno = "15", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Cruz:2021:OTD, author = "Eduardo H. M. Cruz and Matthias Diener and La{\'e}rcio L. Pilla and Philippe O. A. Navaux", title = "Online Thread and Data Mapping Using a Sharing-Aware Memory Management Unit", journal = j-TOMPECS, volume = "5", number = "4", pages = "16:1--16:28", month = mar, year = "2021", CODEN = "????", DOI = "https://doi.org/10.1145/3433687", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sun Mar 28 07:27:07 MDT 2021", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3433687", abstract = "Current and future architectures rely on thread-level parallelism to sustain performance growth. These architectures have introduced a complex memory hierarchy, consisting of several cores organized hierarchically with multiple cache levels and NUMA \ldots{}", acknowledgement = ack-nhfb, articleno = "16", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Al-Abbasi:2021:VJS, author = "Abubakr O. Al-Abbasi and Vaneet Aggarwal", title = "{VidCloud}: Joint Stall and Quality Optimization for Video Streaming over Cloud", journal = j-TOMPECS, volume = "5", number = "4", pages = "17:1--17:32", month = mar, year = "2021", CODEN = "????", DOI = "https://doi.org/10.1145/3442187", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sun Mar 28 07:27:07 MDT 2021", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3442187", abstract = "As video-streaming services have expanded and improved, cloud-based video has evolved into a necessary feature of any successful business for reaching internal and external audiences. In this article, video streaming over distributed storage is \ldots{}", acknowledgement = ack-nhfb, articleno = "17", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Makrani:2021:APM, author = "Hosein Mohamamdi Makrani and Hossein Sayadi and Najmeh Nazari and Sai Mnoj Pudukotai Dinakarrao and Avesta Sasan and Tinoosh Mohsenin and Setareh Rafatirad and Houman Homayoun", title = "Adaptive Performance Modeling of Data-intensive Workloads for Resource Provisioning in Virtualized Environment", journal = j-TOMPECS, volume = "5", number = "4", pages = "18:1--18:24", month = mar, year = "2021", CODEN = "????", DOI = "https://doi.org/10.1145/3442696", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Sun Mar 28 07:27:07 MDT 2021", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3442696", abstract = "The processing of data-intensive workloads is a challenging and time-consuming task that often requires massive infrastructure to ensure fast data analysis. The cloud platform is the most popular and powerful scale-out infrastructure to perform big data \ldots{}", acknowledgement = ack-nhfb, articleno = "18", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Qin:2021:OOA, author = "Tiancheng Qin and S. Rasoul Etesami", title = "Optimal Online Algorithms for File-Bundle Caching and Generalization to Distributed Caching", journal = j-TOMPECS, volume = "6", number = "1", pages = "1:1--1:23", month = mar, year = "2021", CODEN = "????", DOI = "https://doi.org/10.1145/3445028", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Wed Mar 2 06:32:08 MST 2022", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3445028", abstract = "We consider a generalization of the standard cache problem called file-bundle caching, where different queries (tasks), each containing $ l \eq 1 $ files, sequentially arrive. An online algorithm that does not know the sequence of queries ahead of time must \ldots{}", acknowledgement = ack-nhfb, articleno = "1", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Domingues:2021:RHC, author = "Guilherme Domingues and Gabriel Mendon{\c{c}}a and Edmundo {De Souza E.Silva} and Rosa M. M. Le{\~a}o and Daniel S. Menasch{\'e} and Ori Rottenstreich and Mostafa Dehghan and Don Towsley", title = "The Role of Hysteresis in Caching Systems", journal = j-TOMPECS, volume = "6", number = "1", pages = "2:1--2:38", month = jun, year = "2021", CODEN = "????", DOI = "https://doi.org/10.1145/3450564", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Wed Mar 2 06:32:08 MST 2022", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3450564", abstract = "Caching is a fundamental element of networking systems since the early days of the Internet. By filtering requests toward custodians, caches reduce the bandwidth required by the latter and the delay experienced by clients. The requests that are not \ldots{}", acknowledgement = ack-nhfb, articleno = "2", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Liu:2021:DES, author = "Zhengchun Liu and Rajkumar Kettimuthu and Joaquin Chung and Rachana Ananthakrishnan and Michael Link and Ian Foster", title = "Design and Evaluation of a Simple Data Interface for Efficient Data Transfer across Diverse Storage", journal = j-TOMPECS, volume = "6", number = "1", pages = "3:1--3:25", month = jun, year = "2021", CODEN = "????", DOI = "https://doi.org/10.1145/3452007", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Wed Mar 2 06:32:08 MST 2022", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3452007", abstract = "Modern science and engineering computing environments often feature storage systems of different types, from parallel file systems in high-performance computing centers to object stores operated by cloud providers. To enable easy, reliable, secure, and \ldots{}", acknowledgement = ack-nhfb, articleno = "3", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Nemati:2021:HBV, author = "Hani Nemati and Seyed Vahid Azhari and Mahsa Shakeri and Michel Dagenais", title = "Host-Based Virtual Machine Workload Characterization Using Hypervisor Trace Mining", journal = j-TOMPECS, volume = "6", number = "1", pages = "4:1--4:25", month = jun, year = "2021", CODEN = "????", DOI = "https://doi.org/10.1145/3460197", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Wed Mar 2 06:32:08 MST 2022", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3460197", abstract = "Cloud computing is a fast-growing technology that provides on-demand access to a pool of shared resources. This type of distributed and complex environment requires advanced resource management solutions that could model virtual machine (VM) behavior. \ldots{}", acknowledgement = ack-nhfb, articleno = "4", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Jiang:2021:CCS, author = "Bo Jiang and Philippe Nain and Don Towsley", title = "Covert Cycle Stealing in a Single {FIFO} Server", journal = j-TOMPECS, volume = "6", number = "2", pages = "5:1--5:33", month = jun, year = "2021", CODEN = "????", DOI = "https://doi.org/10.1145/3462774", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Wed Mar 2 06:32:09 MST 2022", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3462774", abstract = "Consider a setting where Willie generates a Poisson stream of jobs and routes them to a single server that follows the first-in first-out discipline. Suppose there is an adversary Alice, who desires to receive service without being detected. We ask the \ldots{}", acknowledgement = ack-nhfb, articleno = "5", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Sonenberg:2021:PAW, author = "Nikki Sonenberg and Grzegorz Kielanski and Benny {Van Houdt}", title = "Performance Analysis of Work Stealing in Large-scale Multithreaded Computing", journal = j-TOMPECS, volume = "6", number = "2", pages = "6:1--6:28", month = jun, year = "2021", CODEN = "????", DOI = "https://doi.org/10.1145/3470887", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Wed Mar 2 06:32:09 MST 2022", bibsource = "http://www.math.utah.edu/pub/tex/bib/multithreading.bib; http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3470887", abstract = "Randomized work stealing is used in distributed systems to increase performance and improve resource utilization. In this article, we consider randomized work stealing in a large system of homogeneous processors where parent jobs spawn child jobs that can \ldots{}", acknowledgement = ack-nhfb, articleno = "6", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Marques:2021:MRM, author = "Diogo Marques and Aleksandar Ilic and Leonel Sousa", title = "Mansard Roofline Model: Reinforcing the Accuracy of the Roofs", journal = j-TOMPECS, volume = "6", number = "2", pages = "7:1--7:23", month = jun, year = "2021", CODEN = "????", DOI = "https://doi.org/10.1145/3475866", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Wed Mar 2 06:32:09 MST 2022", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3475866", abstract = "Continuous enhancements and diversity in modern multi-core hardware, such as wider and deeper core pipelines and memory subsystems, bring to practice a set of hard-to-solve challenges when modeling their upper-bound capabilities and identifying the main \ldots{}", acknowledgement = ack-nhfb, articleno = "7", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Narayana:2021:RER, author = "V. S. Ch Lakshmi Narayana and Sharayu Moharir and Nikhil Karamchandani", title = "On Renting Edge Resources for Service Hosting", journal = j-TOMPECS, volume = "6", number = "2", pages = "8:1--8:30", month = jun, year = "2021", CODEN = "????", DOI = "https://doi.org/10.1145/3478433", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Wed Mar 2 06:32:09 MST 2022", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3478433", abstract = "The rapid proliferation of shared edge computing platforms has enabled application service providers to deploy a wide variety of services with stringent latency and high bandwidth requirements. A key advantage of these platforms is that they provide pay-. \ldots{}", acknowledgement = ack-nhfb, articleno = "8", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Engelmann:2021:CRA, author = "Anna Engelmann and Admela Jukan", title = "A Combinatorial Reliability Analysis of Generic Service Function Chains in Data Center Networks", journal = j-TOMPECS, volume = "6", number = "3", pages = "9:1--9:24", month = sep, year = "2021", CODEN = "????", DOI = "https://doi.org/10.1145/3477046", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Wed Mar 2 06:32:09 MST 2022", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3477046", abstract = "In data center networks, the reliability of Service Function Chain (SFC)-an end-to-end service presented by a chain of virtual network functions (VNFs)-is a complex and specific function of placement, configuration, and application requirements, both in \ldots{}", acknowledgement = ack-nhfb, articleno = "9", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Fan:2021:PAI, author = "Caixiang Fan and Sara Ghaemi and Hamzeh Khazaei and Yuxiang Chen and Petr Musilek", title = "Performance Analysis of the {IOTA} {DAG}-Based Distributed Ledger", journal = j-TOMPECS, volume = "6", number = "3", pages = "10:1--10:20", month = sep, year = "2021", CODEN = "????", DOI = "https://doi.org/10.1145/3485188", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Wed Mar 2 06:32:09 MST 2022", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3485188", abstract = "Distributed ledgers (DLs) provide many advantages over centralized solutions in Internet of Things projects, including but not limited to improved security, transparency, and fault tolerance. To leverage DLs at scale, their well-known limitation (i.e., \ldots{})", acknowledgement = ack-nhfb, articleno = "10", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Geissler:2021:DTM, author = "Stefan Geissler and Stanislav Lange and Leonardo Linguaglossa and Dario Rossi and Thomas Zinner and Tobias Hossfeld", title = "Discrete-Time Modeling of {NFV} Accelerators that Exploit Batched Processing", journal = j-TOMPECS, volume = "6", number = "3", pages = "11:1--11:27", month = sep, year = "2021", CODEN = "????", DOI = "https://doi.org/10.1145/3488243", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Wed Mar 2 06:32:09 MST 2022", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3488243", abstract = "Network Functions Virtualization (NFV) is among the latest network revolutions, promising increased flexibility and avoiding network ossification. At the same time, all-software NFV implementations on commodity hardware raise performance issues when \ldots{}", acknowledgement = ack-nhfb, articleno = "11", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Gaeta:2021:MNI, author = "Rossano Gaeta and Marco Grangetto", title = "Malicious Node Identification in Coded Distributed Storage Systems under Pollution Attacks", journal = j-TOMPECS, volume = "6", number = "3", pages = "12:1--12:27", month = sep, year = "2021", CODEN = "????", DOI = "https://doi.org/10.1145/3491062", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Wed Mar 2 06:32:09 MST 2022", bibsource = "http://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3491062", abstract = "In coding-based distributed storage systems (DSSs), a set of storage nodes (SNs) hold coded fragments of a data unit that collectively allow one to recover the original information. It is well known that data modification (a.k.a. pollution attack) is the \ldots{}", acknowledgement = ack-nhfb, articleno = "12", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Du:2021:ADL, author = "Bingqian Du and Zhiyi Huang and Chuan Wu", title = "Adversarial Deep Learning for Online Resource Allocation", journal = j-TOMPECS, volume = "6", number = "4", pages = "13:1--13:??", month = dec, year = "2021", CODEN = "????", DOI = "https://doi.org/10.1145/3494526", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:40 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3494526", abstract = "Online algorithms are an important branch in algorithm design. Designing online algorithms with a bounded competitive ratio (in terms of worst-case performance) can be hard and usually relies on problem-specific assumptions. Inspired by adversarial \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "13", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Mansfield:2021:MCT, author = "Sam Mansfield and Kerry Veenstra and Katia Obraczka", title = "Modeling Communication over Terrain for Realistic Simulation of Outdoor Sensor Network Deployments", journal = j-TOMPECS, volume = "6", number = "4", pages = "14:1--14:??", month = dec, year = "2021", CODEN = "????", DOI = "https://doi.org/10.1145/3510306", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:40 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3510306", abstract = "Popular wireless network simulators have few available propagation models for outdoor Internet of Things applications. Of the available models, only a handful use real terrain data, yet an inaccurate propagation model can skew the results of simulations. \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "14", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Rubattu:2021:PUR, author = "Claudio Rubattu and Francesca Palumbo and Shuvra S. Bhattacharyya and Maxime Pelcat", title = "{PathTracer}: Understanding Response Time of Signal Processing Applications on Heterogeneous {MPSoCs}", journal = j-TOMPECS, volume = "6", number = "4", pages = "15:1--15:??", month = dec, year = "2021", CODEN = "????", DOI = "https://doi.org/10.1145/3513003", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:40 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3513003", abstract = "In embedded and cyber-physical systems, the design of a desired functionality under constraints increasingly requires parallel execution of a set of tasks on a heterogeneous architecture. The nature of such parallel systems complicates the process of \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "15", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Giannakas:2021:MBN, author = "Theodoros Giannakas and Anastasios Giovanidis and Thrasyvoulos Spyropoulos", title = "{MDP}-based Network Friendly Recommendations", journal = j-TOMPECS, volume = "6", number = "4", pages = "16:1--16:??", month = dec, year = "2021", CODEN = "????", DOI = "https://doi.org/10.1145/3513131", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:40 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3513131", abstract = "Controlling the network cost by delivering popular content to users, as well as improving streaming quality and overall user experience, have been key goals for content providers (CP) in recent years. While proposals to improve performance, through \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "16", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Bayat:2022:BWS, author = "Niloofar Bayat and Richard T. B. Ma and Vishal Misra and Dan Rubenstein", title = "Big Winners and Small Losers of Zero-rating", journal = j-TOMPECS, volume = "7", number = "1", pages = "1:1--1:??", month = mar, year = "2022", CODEN = "????", DOI = "https://doi.org/10.1145/3539731", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:41 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3539731", abstract = "An objective of network neutrality is to design regulations for the Internet and ensure that it remains a public, open platform where innovations can thrive. While there is broad agreement that preserving the content quality of service falls under the \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "1", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Liu:2022:RQR, author = "Bai Liu and Qiaomin Xie and Eytan Modiano", title = "{RL-QN}: a Reinforcement Learning Framework for Optimal Control of Queueing Systems", journal = j-TOMPECS, volume = "7", number = "1", pages = "2:1--2:??", month = mar, year = "2022", CODEN = "????", DOI = "https://doi.org/10.1145/3529375", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:41 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3529375", abstract = "With the rapid advance of information technology, network systems have become increasingly complex and hence the underlying system dynamics are often unknown or difficult to characterize. Finding a good network control policy is of significant importance \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "2", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Hebbar:2022:PED, author = "Ranjan Hebbar and Aleksandar Milenkovi'c", title = "{PMU}-Events-Driven {DVFS} Techniques for Improving Energy Efficiency of Modern Processors", journal = j-TOMPECS, volume = "7", number = "1", pages = "3:1--3:??", month = mar, year = "2022", CODEN = "????", DOI = "https://doi.org/10.1145/3538645", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:41 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3538645", abstract = "This paper describes the results of our measurement-based study, conducted on an Intel Core i7 processor running the SPEC CPU2017 benchmark suites, that evaluates the impact of dynamic voltage frequency scaling (DVFS) on performance (P), energy efficiency \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "3", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Sondur:2022:PHI, author = "Sanjeev Sondur and Krishna Kant", title = "Performance Health Index for Complex Cyber Infrastructures", journal = j-TOMPECS, volume = "7", number = "1", pages = "4:1--4:??", month = mar, year = "2022", CODEN = "????", DOI = "https://doi.org/10.1145/3538646", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:41 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3538646", abstract = "Most IT systems depend on a set of configuration variables (CVs), expressed as a name/value pair that collectively defines the resource allocation for the system. While the ill effects of misconfiguration or improper resource allocation are well-known, \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "4", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Panigrahy:2022:NUB, author = "Nitish K. Panigrahy and Philippe Nain and Giovanni Neglia and Don Towsley", title = "A New Upper Bound on Cache Hit Probability for Non-Anticipative Caching Policies", journal = j-TOMPECS, volume = "7", number = "2--4", pages = "5:1--5:??", month = dec, year = "2022", CODEN = "????", DOI = "https://doi.org/10.1145/3547332", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:41 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3547332", abstract = "Caching systems have long been crucial for improving the performance of a wide variety of network and web-based online applications. In such systems, end-to-end application performance heavily depends on the fraction of objects transferred from the cache, \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "5", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Panigrahy:2022:AEP, author = "Nitish K. Panigrahy and Thirupathaiah Vasantam and Prithwish Basu and Don Towsley and Ananthram Swami and Kin K. Leung", title = "On the Analysis and Evaluation of Proximity-based Load-balancing Policies", journal = j-TOMPECS, volume = "7", number = "2--4", pages = "6:1--6:??", month = dec, year = "2022", CODEN = "????", DOI = "https://doi.org/10.1145/3549933", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:41 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3549933", abstract = "Distributed load balancing is the act of allocating jobs among a set of servers as evenly as possible. The static interpretation of distributed load balancing leads to formulating the load-balancing problem as a classical balls-and-bins problem with jobs \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "6", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Islam:2022:FLP, author = "Farhana Islam and Dorina Petriu and Murray Woodside", title = "Focused Layered Performance Modelling by Aggregation", journal = j-TOMPECS, volume = "7", number = "2--4", pages = "7:1--7:??", month = dec, year = "2022", CODEN = "????", DOI = "https://doi.org/10.1145/3549539", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:41 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3549539", abstract = "Performance models of server systems, based on layered queues, may be very complex. This is particularly true for cloud-based systems based on microservices, which may have hundreds of distinct components, and for models derived by automated data \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "7", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Vardoyan:2023:CRB, author = "Gayane Vardoyan and Philippe Nain and Saikat Guha and Don Towsley", title = "On the Capacity Region of Bipartite and Tripartite Entanglement Switching", journal = j-TOMPECS, volume = "8", number = "1--2", pages = "1:1--1:??", month = jun, year = "2023", CODEN = "????", DOI = "https://doi.org/10.1145/3571809", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:43 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3571809", abstract = "We study a quantum entanglement distribution switch serving a set of users in a star topology with equal-length links. The quantum switch, much like a quantum repeater, can perform entanglement swapping to extend \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "1", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Zhao:2023:PPL, author = "Tianming Zhao and Wei Li and Boyu Qin and Ling Wang and Albert Y. Zomaya", title = "Pulsed Power Load Coordination in Mission- and Time-critical Cyber-physical Systems", journal = j-TOMPECS, volume = "8", number = "1--2", pages = "2:1--2:??", month = jun, year = "2023", CODEN = "????", DOI = "https://doi.org/10.1145/3573197", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:43 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3573197", abstract = "Many mission- and time-critical cyber-physical systems deploy an isolated power system for their power supply. Under extreme conditions, the power system must process critical missions by maximizing the \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "2", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Houdt:2023:CNP, author = "Benny {Van Houdt}", title = "On the Cost of Near-Perfect Wear Leveling in Flash-Based {SSDs}", journal = j-TOMPECS, volume = "8", number = "1--2", pages = "3:1--3:??", month = jun, year = "2023", CODEN = "????", DOI = "https://doi.org/10.1145/3576855", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:43 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3576855", abstract = "Wear leveling (WL) techniques in flash-based SSDs aim at distributing the erase cycles as uniformly as possible across the memory blocks within the SSD to extend its life span. The downside of any WL technique is that \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "3", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Tseng:2023:TTF, author = "Shih-hao Tseng and Soojean Han and Adam Wierman", title = "Trading Throughput for Freshness: Freshness-aware Traffic Engineering and In-Network Freshness Control", journal = j-TOMPECS, volume = "8", number = "1--2", pages = "4:1--4:??", month = jun, year = "2023", CODEN = "????", DOI = "https://doi.org/10.1145/3576919", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:43 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3576919", abstract = "With the advent of the Internet of Things (IoT), applications are becoming increasingly dependent on networks to not only transmit content at high throughput but also deliver it when it is fresh, i.e., \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "4", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Chaudhary:2023:DSP, author = "Kiran Chaudhary and Veeraruna Kavitha and Jayakrishnan Nair", title = "Dynamic Scheduling in a Partially Fluid, Partially Lossy Queueing System", journal = j-TOMPECS, volume = "8", number = "3", pages = "5:1--5:??", month = sep, year = "2023", CODEN = "????", DOI = "https://doi.org/10.1145/3582884", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:44 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3582884", abstract = "We consider a single server queueing system with two classes of jobs: eager jobs with small sizes that require service to begin almost immediately upon arrival, and tolerant jobs with larger sizes that can wait for service. While blocking probability is \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "5", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Wu:2023:DPD, author = "Xiaohu Wu and Francesco {De Pellegrini} and Giuliano Casale", title = "Delay and Price Differentiation in Cloud Computing: a Service Model, Supporting Architectures, and Performance", journal = j-TOMPECS, volume = "8", number = "3", pages = "6:1--6:??", month = sep, year = "2023", CODEN = "????", DOI = "https://doi.org/10.1145/3592852", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:44 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3592852", abstract = "Many cloud service providers (CSPs) offer an on-demand service with a small delay. Motivated by the reality of cloud ecosystems, we study non-interruptible services and consider a differentiated service model to complement the existing market by offering \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "6", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Carballo-Hernandez:2023:FSP, author = "Walther Carballo-Hern{\'a}ndez and Maxime Pelcat and Shuvra S. Bhattacharyya and Ricardo Carmona Gal{\'a}n and Fran{\c{c}}ois Berry", title = "Flydeling: Streamlined Performance Models for Hardware Acceleration of {CNNs} through System Identification", journal = j-TOMPECS, volume = "8", number = "3", pages = "7:1--7:??", month = sep, year = "2023", CODEN = "????", DOI = "https://doi.org/10.1145/3594870", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:44 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3594870", abstract = "The introduction of deep learning algorithms, such as Convolutional Neural Networks (CNNs) in many near-sensor embedded systems, opens new challenges in terms of energy efficiency and hardware performance. An emerging solution to address these challenges \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "7", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Dai:2023:LOR, author = "Wenkai Dai and Klaus-Tycho Foerster and David Fuchssteiner and Stefan Schmid", title = "Load-optimization in Reconfigurable Data-center Networks: Algorithms and Complexity of Flow Routing", journal = j-TOMPECS, volume = "8", number = "3", pages = "8:1--8:??", month = sep, year = "2023", CODEN = "????", DOI = "https://doi.org/10.1145/3597200", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:44 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3597200", abstract = "Emerging reconfigurable data centers introduce unprecedented flexibility in how the physical layer can be programmed to adapt to current traffic demands. These reconfigurable topologies are commonly hybrid, consisting of static and reconfigurable links, \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "8", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Tournaire:2023:ECO, author = "Thomas Tournaire and Hind Castel-Taleb and Emmanuel Hyon", title = "Efficient Computation of Optimal Thresholds in Cloud Auto-scaling Systems", journal = j-TOMPECS, volume = "8", number = "4", pages = "9:1--9:??", month = dec, year = "2023", CODEN = "????", DOI = "https://doi.org/10.1145/3603532", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:44 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3603532", abstract = "We consider a horizontal and dynamic auto-scaling technique in a cloud system where virtual machines hosted on a physical node are turned on and off to minimise energy consumption while meeting performance requirements. Finding cloud management policies \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "9", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Alavani:2023:PAM, author = "Gargi Alavani and Jineet Desai and Snehanshu Saha and Santonu Sarkar", title = "Program Analysis and Machine Learning-based Approach to Predict Power Consumption of {CUDA} Kernel", journal = j-TOMPECS, volume = "8", number = "4", pages = "10:1--10:??", month = dec, year = "2023", CODEN = "????", DOI = "https://doi.org/10.1145/3603533", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:44 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3603533", abstract = "The General Purpose Graphics Processing Unit has secured a prominent position in the High-Performance Computing world due to its performance gain and programmability. Understanding the relationship between Graphics Processing Unit (GPU) power consumption \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "10", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Salem:2023:NRC, author = "Tareq Si Salem and Giovanni Neglia and Stratis Ioannidis", title = "No-regret Caching via Online Mirror Descent", journal = j-TOMPECS, volume = "8", number = "4", pages = "11:1--11:??", month = dec, year = "2023", CODEN = "????", DOI = "https://doi.org/10.1145/3605209", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:44 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3605209", abstract = "We study an online caching problem in which requests can be served by a local cache to avoid retrieval costs from a remote server. The cache can update its state after a batch of requests and store an arbitrarily small fraction of each file. We study no-. \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "11", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{S:2023:OPS, author = "Ashok Krishnan K. S. and Chandramani Singh and Siva Theja Maguluri and Parimal Parag", title = "Optimal Pricing in a Single Server System", journal = j-TOMPECS, volume = "8", number = "4", pages = "12:1--12:??", month = dec, year = "2023", CODEN = "????", DOI = "https://doi.org/10.1145/3607252", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:44 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3607252", abstract = "We study optimal pricing in a single server queue when the customers valuation of service depends on their waiting time. In particular, we consider a very general model, where the customer valuations are random and are sampled from a distribution that \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "12", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Amparore:2024:CPN, author = "Elvio Amparore and Marco Beccuti and Paolo Castagno and Simone Pernice and Giuliana Franceschinis and Marzio Pennisi", title = "From Compositional {Petri} Net Modeling to Macro and Micro Simulation by Means of Stochastic Simulation and Agent-Based Models", journal = j-TOMPECS, volume = "9", number = "1", pages = "1:1--1:??", month = mar, year = "2024", CODEN = "????", DOI = "https://doi.org/10.1145/3617681", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:45 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3617681", abstract = "Computational modeling has become a widespread approach for studying real-world phenomena by using different modeling perspectives, in particular, the microscopic point of view concentrates on the behavior of the single components and their interactions \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "1", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Borusu:2024:OPS, author = "V. S. Ch Lakshmi Narayana Borusu and Mohit Agarwala and Sri Prakash R. and Nikhil Karamchandani and Sharayu Moharir", title = "Online Partial Service Hosting at the Edge", journal = j-TOMPECS, volume = "9", number = "1", pages = "2:1--2:??", month = mar, year = "2024", CODEN = "????", DOI = "https://doi.org/10.1145/3616866", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:45 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3616866", abstract = "We consider the problem of service hosting where an application provider can dynamically rent edge computing resources and serve user requests from the edge to deliver a better quality of service. A key novelty of this work is that we allow the service to \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "2", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Brandwajn:2024:AMN, author = "Alexandre Brandwajn and Thomas Begin", title = "Approximation Method for a Non-preemptive Multiserver Queue with Quasi-{Poisson} Arrivals", journal = j-TOMPECS, volume = "9", number = "1", pages = "3:1--3:??", month = mar, year = "2024", CODEN = "????", DOI = "https://doi.org/10.1145/3624474", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:45 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3624474", abstract = "We consider a non-preemptive multiserver queue with multiple priority classes. We assume distinct exponentially distributed service times and separate quasi-Poisson arrival processes with a predefined maximum number of requests that can be present in the \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "3", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Gupta:2024:CCE, author = "Jit Gupta and Krishna Kant and Amitangshu Pal and Joyanta Biswas", title = "Configuring and Coordinating End-to-end {QoS} for Emerging Storage Infrastructure", journal = j-TOMPECS, volume = "9", number = "1", pages = "4:1--4:??", month = mar, year = "2024", CODEN = "????", DOI = "https://doi.org/10.1145/3631606", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:45 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3631606", abstract = "Modern data center storage systems are invariably networked to allow for consolidation and flexible management of storage. They also include high-performance storage devices based on flash or other emerging technologies, generally accessed through low-. \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "4", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Zhang:2024:VMC, author = "Yixuan Zhang and Shuyu Zheng and Haoyu Wang and Lei Wu and Gang Huang and Xuanzhe Liu", title = "{VM} Matters: a Comparison of {WASM VMs} and {EVMs} in the Performance of Blockchain Smart Contracts", journal = j-TOMPECS, volume = "9", number = "2", pages = "5:1--5:??", month = jun, year = "2024", CODEN = "????", DOI = "https://doi.org/10.1145/3641103", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:45 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3641103", abstract = "Beyond an emerging popular web applications runtime supported in almost all commodity browsers, WebAssembly (WASM) is further regarded to be the next-generation execution environment for blockchain-based applications. Indeed, many popular blockchain \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "5", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Olliaro:2024:PFN, author = "Diletta Olliaro and Giuliano Casale and Andrea Marin and Sabina Rossi", title = "A Product-form Network for Systems with Job Stealing Policies", journal = j-TOMPECS, volume = "9", number = "2", pages = "6:1--6:??", month = jun, year = "2024", CODEN = "????", DOI = "https://doi.org/10.1145/3643845", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:45 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3643845", abstract = "In queueing networks, product-form solutions are of fundamental importance to efficiently compute performance metrics in complex models of computer systems. The product-form property entails that the steady-state probabilities of the joint stochastic \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "6", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Marin:2024:QNM, author = "Andrea Marin and Michela Meo and Matteo Sereno and Marco Ajmone Marsan", title = "Queuing Network Models of Multiservice {RANs}", journal = j-TOMPECS, volume = "9", number = "2", pages = "7:1--7:??", month = jun, year = "2024", CODEN = "????", DOI = "https://doi.org/10.1145/3649307", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:45 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3649307", abstract = "In this article, we present a new queuing network model for the analysis of a portion of a radio access network (RAN) comprising macro cell base stations (BSs) and small cell BSs offering ``streaming'' and ``elastic'' services. Streaming services require a \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "7", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", } @Article{Anselmi:2024:LBJ, author = "Jonatha Anselmi and Josu Doncel", title = "Load Balancing with Job-Size Testing: Performance Improvement or Degradation?", journal = j-TOMPECS, volume = "9", number = "2", pages = "8:1--8:??", month = jun, year = "2024", CODEN = "????", DOI = "https://doi.org/10.1145/3651154", ISSN = "2376-3639 (print), 2376-3647 (electronic)", ISSN-L = "2376-3639", bibdate = "Tue Apr 30 13:20:45 MDT 2024", bibsource = "https://www.math.utah.edu/pub/tex/bib/tompecs.bib", URL = "https://dl.acm.org/doi/10.1145/3651154", abstract = "In the context of decision making under explorable uncertainty, scheduling with testing is a powerful technique used in the management of computer systems to improve performance via better job-dispatching decisions. Upon job arrival, a scheduler may run \ldots{}", acknowledgement = ack-nhfb, ajournal = "ACM Trans. Model. Perform. Eval. Comput. Syst.", articleno = "8", fjournal = "ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)", journal-URL = "https://dl.acm.org/loi/tompecs", }