Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems最新文献_第5页

Unleashing the Power of Paying Multiplexing Only Once in Stochastic Network Calculus 在随机网络演算中释放一次支付复用的力量

Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2022-06-06 DOI: 10.1145/3489048.3530964

A. Bouillard, Paul Nikolaus, J. Schmitt

{"title":"Unleashing the Power of Paying Multiplexing Only Once in Stochastic Network Calculus","authors":"A. Bouillard, Paul Nikolaus, J. Schmitt","doi":"10.1145/3489048.3530964","DOIUrl":"https://doi.org/10.1145/3489048.3530964","url":null,"abstract":"The stochastic network calculus (SNC) holds promise as a versatile and uniform framework to calculate probabilistic performance bounds in networks of queues. A great challenge to accurate bounds and efficient calculations are stochastic dependencies between flows due to resource sharing inside the network. However, by carefully utilizing the basic SNC concepts in the network analysis the necessity of taking these dependencies into account can be minimized. To that end, we unleash the power of the pay multiplexing only once principle (PMOO, known from the deterministic network calculus) in the SNC analysis. We choose an analytic combinatorics presentation of the results in order to ease complex calculations. In tree-reducible networks, a subclass of general feedforward networks, we obtain an effective analysis in terms of avoiding the need to take internal flow dependencies into account. In a comprehensive numerical evaluation, we demonstrate how this unleashed PMOO analysis can reduce the known gap between simulations and SNC calculations significantly, and how it favourably compares to state-of-the art SNC calculations in terms of accuracy and computational effort. Motivated by these promising results, we also consider general feedforward networks, when some flow dependencies have to be taken into account. To that end, the unleashed PMOO analysis is extended to the partially dependent case and a case study of a canonical topology, known as the diamond network, is provided, again displaying favourable results over the state of the art.","PeriodicalId":264598,"journal":{"name":"Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131583902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Competitive Algorithms for Online Multidimensional Knapsack Problems 在线多维背包问题的竞争算法

Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2022-06-06 DOI: 10.1145/3489048.3522627

L. Yang, A. Zeynali, M. Hajiesmaili, R. Sitaraman, D. Towsley

{"title":"Competitive Algorithms for Online Multidimensional Knapsack Problems","authors":"L. Yang, A. Zeynali, M. Hajiesmaili, R. Sitaraman, D. Towsley","doi":"10.1145/3489048.3522627","DOIUrl":"https://doi.org/10.1145/3489048.3522627","url":null,"abstract":"In this work, we study the online multidimensional knapsack problem (called OMdKP) in which there is a knapsack whose capacity is represented in m dimensions, each dimension could have a different capacity. Then, n items with different scalar profit values and m-dimensional weights arrive in an online manner and the goal is to admit or decline items upon their arrival such that the total profit obtained by admitted items is maximized and the capacity of knapsack across all dimensions is respected. This is a natural generalization of the classic single-dimension knapsack problem with several relevant applications such as in virtual machine allocation, job scheduling, and all-or-nothing flow maximization over a graph. We develop an online algorithm for OMdKP that uses an exponential reservation function to make online admission decisions. Our competitive analysis shows that the proposed online algorithm achieves the competitive ratio of O(log (Θ α)), where α is the ratio between the aggregate knapsack capacity and the minimum capacity over a single dimension and θ is the ratio between the maximum and minimum item unit values. We also show that the competitive ratio of our algorithm with exponential reservation function matches the lower bound up to a constant factor.","PeriodicalId":264598,"journal":{"name":"Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114842266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

End-to-end Characterization of Game Streaming Applications on Mobile Platforms 移动平台上游戏流媒体应用的端到端特性分析

Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2022-06-06 DOI: 10.1145/3489048.3522650

Sandeepa Bhuyan, Shulin Zhao, Ziyu Ying, M. Kandemir, C. Das

{"title":"End-to-end Characterization of Game Streaming Applications on Mobile Platforms","authors":"Sandeepa Bhuyan, Shulin Zhao, Ziyu Ying, M. Kandemir, C. Das","doi":"10.1145/3489048.3522650","DOIUrl":"https://doi.org/10.1145/3489048.3522650","url":null,"abstract":"With the advent of 5G, hosting high-quality game streaming applications on mobile devices has become a reality. To our knowledge, no prior study systematically investigates the < QoS, Energy > tuple on the end-to-end game streaming pipeline across the cloud, network, and edge devices to understand the individual contributions of the different pipeline stages. In this paper, we present a comprehensive performance and power analysis of the entire game streaming pipeline through extensive measurements with a high-end workstation mimicking the cloud end, an open-source platform (Moonlight-GameStreaming) emulating the edge device/mobile platform, and two network settings (WiFi and 5G). Our study shows that the rendering stage and the encoding stage at the cloud end are the bottlenecks for 4K streaming. While 5G is certainly more suitable for supporting enhanced video quality with 4K streaming, it is more expensive in terms of power consumption compared to WiFi. Further, the network interface and the decoder units in mobile devices need more energy-efficient design to support high quality games at a lower cost. These observations should help in designing more cost-effective future cloud gaming platforms.","PeriodicalId":264598,"journal":{"name":"Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126634713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Dynamic Regret Minimization for Control of Non-stationary Linear Dynamical Systems 非平稳线性动力系统控制的动态遗憾最小化

Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2022-06-06 DOI: 10.1145/3489048.3522649

Yuwei Luo, Varun Gupta, M. Kolar

{"title":"Dynamic Regret Minimization for Control of Non-stationary Linear Dynamical Systems","authors":"Yuwei Luo, Varun Gupta, M. Kolar","doi":"10.1145/3489048.3522649","DOIUrl":"https://doi.org/10.1145/3489048.3522649","url":null,"abstract":"We consider the problem of controlling a Linear Quadratic Regulator (LQR) system over a finite horizon T with fixed and known cost matrices Q,R, but unknown and non-stationary dynamics At, Bt. The sequence of dynamics matrices can be arbitrary, but with a total variation, VT, assumed to be o(T) and unknown to the controller. Under the assumption that a sequence of stabilizing, but potentially sub-optimal controllers is available for all t, we present an algorithm that achieves the optimal dynamic regret of Õ(VT2/5 T3/5). With piecewise constant dynamics, our algorithm achieves the optimal regret of Õ(√ST) where S is the number of switches. The crux of our algorithm is an adaptive non-stationarity detection strategy, which builds on an approach recently developed for contextual Multi-armed Bandit problems. We also argue that non-adaptive forgetting (e.g., restarting or using sliding window learning with a static window size) may not be regret optimal for the LQR problem, even when the window size is optimally tuned with the knowledge of VT. The main technical challenge in the analysis of our algorithm is to prove that the ordinary least squares (OLS) estimator has a small bias when the parameter to be estimated is non-stationary. Our analysis also highlights that the key motif driving the regret is that the LQR problem is in spirit a bandit problem with linear feedback and locally quadratic cost. This motif is more universal than the LQR problem itself, and therefore we believe our results should find wider application.","PeriodicalId":264598,"journal":{"name":"Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems","volume":"54 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125738992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Toxicity in the Decentralized Web and the Potential for Model Sharing 去中心化网络的毒性和模型共享的潜力

Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2022-04-27 DOI: 10.1145/3489048.3530968

Haris Bin Zia, Aravindh Raman, Ignacio Castro, Anaobi Ishaku Hassan, Emiliano De Cristofaro, Nishanth R. Sastry, Gareth Tyson

{"title":"Toxicity in the Decentralized Web and the Potential for Model Sharing","authors":"Haris Bin Zia, Aravindh Raman, Ignacio Castro, Anaobi Ishaku Hassan, Emiliano De Cristofaro, Nishanth R. Sastry, Gareth Tyson","doi":"10.1145/3489048.3530968","DOIUrl":"https://doi.org/10.1145/3489048.3530968","url":null,"abstract":"The \"Decentralised Web\" (DW) is an evolving concept, which encompasses technologies aimed at providing greater transparency and openness on the web. The DW relies on independent servers (aka instances) that mesh together in a peer-to-peer fashion to deliver a range of services (e.g. micro-blogs, image sharing, video streaming). However, toxic content moderation in this decentralised context is challenging. This is because there is no central entity that can define toxicity, nor a large central pool of data that can be used to build universal classifiers. It is therefore unsurprising that there have been several high-profile cases of the DW being misused to coordinate and disseminate harmful material. Using a dataset of 9.9M posts from 117K users on Pleroma (a popular DW microblogging service), we quantify the presence of toxic content. We find that toxic content is prevalent and spreads rapidly between instances. We show that automating per-instance content moderation is challenging due to the lack of sufficient training data available and the effort required in labelling. We therefore propose and evaluate ModPair, a model sharing system that effectively detects toxic content, gaining an average per-instance macro-F1 score 0.89.","PeriodicalId":264598,"journal":{"name":"Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122021124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Large-System Insensitivity of Zero-Waiting Load Balancing Algorithms 零等待负载均衡算法的大系统不敏感性

Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2022-02-16 DOI: 10.1145/3489048.3526955

Xin Liu, K. Gong, Lei Ying

{"title":"Large-System Insensitivity of Zero-Waiting Load Balancing Algorithms","authors":"Xin Liu, K. Gong, Lei Ying","doi":"10.1145/3489048.3526955","DOIUrl":"https://doi.org/10.1145/3489048.3526955","url":null,"abstract":"This paper studies the sensitivity (or insensitivity) of a class of load balancing algorithms that achieve asymptotic zero-waiting in the sub-Halfin-Whitt regime, named LB-zero. Most existing results on zero-waiting load balancing algorithms assume the service time distribution is exponential. This paper establishes the large-system insensitivity of LB-zero for jobs whose service time follows a Coxian distribution with a finite number of phases. This result suggests that LB-zero achieves asymptotic zero-waiting for a large class of service time distributions. To prove this result, this paper develops a new technique, called \"Iterative State-Space Peeling'' (or ISSP for short). ISSP first identifies an iterative relation between the upper and lower bounds on the queue states and then proves that the system lives near the fixed point of the iterative bounds with a high probability. Based on ISSP, the steady-state distribution of the system is further analyzed by applying Stein's method in the neighborhood of the fixed point. ISSP, like state-space collapse in heavy-traffic analysis, is a general approach that may be used to study other complex stochastic systems.","PeriodicalId":264598,"journal":{"name":"Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115245540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Sequential Fair Allocation: Achieving the Optimal Envy-Efficiency Tradeoff Curve 顺序公平分配:实现最优嫉妒-效率权衡曲线

Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2021-05-11 DOI: 10.1145/3489048.3526951

Sean R. Sinclair, Siddhartha Banerjee, C. Yu

{"title":"Sequential Fair Allocation: Achieving the Optimal Envy-Efficiency Tradeoff Curve","authors":"Sean R. Sinclair, Siddhartha Banerjee, C. Yu","doi":"10.1145/3489048.3526951","DOIUrl":"https://doi.org/10.1145/3489048.3526951","url":null,"abstract":"We consider the problem of dividing limited resources to individuals arriving over T rounds. Each round has a random number of individuals arrive, and individuals can be characterized by their type (i.e. preferences over the different resources). A standard notion of 'fairness' in this setting is that an allocation simultaneously satisfy envy-freeness and efficiency. For divisible resources, when the number of individuals of each type are known upfront, the above desiderata are simultaneously achievable for a large class of utility functions. However, in an online setting when the number of individuals of each type are only revealed round by round, no policy can guarantee these desiderata simultaneously. We show that in the online setting, the two desired properties (envy-freeness and efficiency) are in direct contention, in that any algorithm achieving additive counterfactual envy-freeness up to a factor of LT necessarily suffers a efficiency loss of at least 1 / LT. We complement this uncertainty principle with a simple algorithm, Guarded-Hope, which allocates resources based on an adaptive threshold policy and is able to achieve any fairness-efficiency point on this frontier.","PeriodicalId":264598,"journal":{"name":"Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132505504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 23

On Multivariate Singular Spectrum Analysis and Its Variants 多元奇异谱分析及其变体

Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2020-06-24 DOI: 10.1145/3489048.3526952

Anish Agarwal, Abdullah Alomar, D. Shah

{"title":"On Multivariate Singular Spectrum Analysis and Its Variants","authors":"Anish Agarwal, Abdullah Alomar, D. Shah","doi":"10.1145/3489048.3526952","DOIUrl":"https://doi.org/10.1145/3489048.3526952","url":null,"abstract":"We introduce and analyze a simpler, practically useful variant of multivariate singular spectrum analysis (mSSA), a known time series method to impute (or de-noise) and forecast a multivariate time series. Towards this, we introduce a spatio-temporal factor model to analyze mSSA. This model includes the usual components used to model dynamics in time series analysis, such as trends (low order polynomials), seasonality (finite sum of harmonics), and linear time-invariant systems. We establish that given N time series and T observations per time series, the in-sample prediction error for both imputation and forecasting under mSSA scales as 1/√ min(N, T)T. This is an improvement over: (i) the 1/√T error scaling of SSA, which is the restriction of mSSA to univariate time series; (ii) the 1/min(N, T) error scaling for Temporal Regularized Matrix Factorized (TRMF), a matrix factorization based method for time series prediction. That is, mSSA exploits both the 'temporal' and 'spatial' structure in a multivariate time series. Our experimental results using various benchmark datasets confirm the characteristics of the spatio-temporal factor model and our theoretical findings---our variant of mSSA empirically performs as well or better compared to neural network based time series methods, LSTM and DeepAR.","PeriodicalId":264598,"journal":{"name":"Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134211342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Power of Bonus in Pricing for Crowdsourcing 奖金在众包定价中的作用

Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems Pub Date : 2018-04-09 DOI: 10.1145/3489048.3522633

Suho Shin, Hoyong Choi, Yu Yi, Jungseul Ok

{"title":"Power of Bonus in Pricing for Crowdsourcing","authors":"Suho Shin, Hoyong Choi, Yu Yi, Jungseul Ok","doi":"10.1145/3489048.3522633","DOIUrl":"https://doi.org/10.1145/3489048.3522633","url":null,"abstract":"We consider a simple form of pricing for a crowdsourcing system, where pricing policy is published a priori, and workers then decide their task acceptance. Such a pricing form is widely adopted in practice for its simplicity, e.g., Amazon Mechanical Turk, although additional sophistication to pricing rule can enhance budget efficiency. With the goal of designing efficient and simple pricing rules, we study the impact of the following two design features in pricing policies: (i) personalization tailoring policy worker-by-worker and (ii) bonus payment to qualified task completion. In the Bayesian setting, where the only prior distribution of workers' profiles is available, we first study the Price of Agnosticism (PoA) that quantifies the utility gap between personalized and common pricing policies. We show that PoA is bounded within a constant factor under some mild conditions, and the impact of bonus is essential in common pricing. These analytic results imply that complex personalized pricing can be replaced by simple common pricing once it is equipped with a proper bonus payment. To provide insights on efficient common pricing, we then study the efficient mechanisms of bonus payment for several profile distribution regimes which may exist in practice. We provide primitive experiments on Amazon Mechanical Turk, which support our analytical findings[5].","PeriodicalId":264598,"journal":{"name":"Abstract Proceedings of the 2022 ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125593436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3