ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)最新文献_第6页

Mean-Field Analysis of Coding Versus Replication in Large Data Storage Systems 大数据存储系统中编码与复制的平均场分析

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2018-02-13 DOI: 10.1145/3159172

Bin Li, A. Ramamoorthy, R. Srikant

{"title":"Mean-Field Analysis of Coding Versus Replication in Large Data Storage Systems","authors":"Bin Li, A. Ramamoorthy, R. Srikant","doi":"10.1145/3159172","DOIUrl":"https://doi.org/10.1145/3159172","url":null,"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.","PeriodicalId":105474,"journal":{"name":"ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124278764","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: 8

List of Reviewers 审稿人名单

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2017-12-21 DOI: 10.1145/3162084

A. Abouzeid

{"title":"List of Reviewers","authors":"A. Abouzeid","doi":"10.1145/3162084","DOIUrl":"https://doi.org/10.1145/3162084","url":null,"abstract":"Alhussein Abouzeid David Aikema Salam Akoum Jussara Almeida Amani Alonazi Hani Mohamed Alzaid Ganesh Ananthanarayanan Leonardo Aniello Christos Antonopoulos Danilo Ardagna Alberto Avritzer Urtzi Ayesta Bita Azimdoost Abdel-Hameed Badawy Albert Banchs Chadi Barakat Michael Alexander Beck Ladjel Bellatreche Ramon Bertram Andrea Bianco Carsten Binnig Sergey Blagodurov Alberto Blanc Bartek Blaszczyszyn Gideon Blocq Tejas Bodas Greg Bollella Alex Borges Joost Bosman Peter Buchholz Wojtek Burakowski Hector Cancela Valeria Cardellini Trevor Carlson Laura Carrington Giuliano Casale Henri Casanova Andrew Cassidy Juan Cebrian Fabio Cecchi Minghua Chen Lydia Chen Lizhong Chen Feng Chen Niangjun Chen Yuan Chen Peng Cheng Lucy Cherkasova Carla Fabiana Chiasserini Tiberiu Chis Dah Ming Chiu Jerry Chou Cheng-Fu Chou Nicaise Choungmo Fofack Anthony Chronopoulos Nikolaos Chrysos Xiaowen Chu Gianfranco Ciardo Florin Ciucu Wang Cong Gianni Conte Ana Paula Couto Silva Alan Cox Juan Cruz Charlie Curtsinger Jinal Dalal Hermann De Meer Koen De Turck Mostafa Dehghan Matthias Diener Antonis Dimakis Ioannis Dimitriou Xiaoning Ding Ming Ding Benjamin Doerr Bin Dong Constantine Dovrolis Douglas Down Idilio Drago Parijat Dube Daniel Dubois Susanna Donatelli Mahmoud El Chamie Sameh Elnikety Constantinos Evangelinos Stijn Eyerman Kaniz Fatema Markus Fidler Giuliana Franceschinis Christine Fricker Maurice Gagnaire Richard Gail Anshul Gandhi Kristen Gardner Michele Garetto Nicolas Gast Paolo Giaccone Daniel Gmach Jorge Gonzalez-Dominguez Sergey Gorinsky Marco Gribaudo Rean Griffith Yanfei Guo Aayush Gupta Varun Gupta Hamed Haddadi Mohammad-Hassan Hajiesmaili Emir Halepovic","PeriodicalId":105474,"journal":{"name":"ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128169224","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: 0

Resource Auto-Scaling and Sparse Content Replication for Video Storage Systems 视频存储系统的资源自动扩展和稀疏内容复制

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2017-11-13 DOI: 10.1145/3079045

Di Niu, Hong Xu, Baochun Li

{"title":"Resource Auto-Scaling and Sparse Content Replication for Video Storage Systems","authors":"Di Niu, Hong Xu, Baochun Li","doi":"10.1145/3079045","DOIUrl":"https://doi.org/10.1145/3079045","url":null,"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 L1-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.","PeriodicalId":105474,"journal":{"name":"ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121496533","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

What You Lose When You Snooze 当你打盹时你会失去什么

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2017-09-27 DOI: 10.1145/3149007

Elisabetta Biondi, C. Boldrini, A. Passarella, M. Conti

{"title":"What You Lose When You Snooze","authors":"Elisabetta Biondi, C. Boldrini, A. Passarella, M. Conti","doi":"10.1145/3149007","DOIUrl":"https://doi.org/10.1145/3149007","url":null,"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.","PeriodicalId":105474,"journal":{"name":"ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134176362","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

Behavioral Model of IEEE 802.15.4 Beacon-Enabled Mode Based on Colored Petri Net 基于有色Petri网的IEEE 802.15.4信标使能模式行为模型

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2017-09-18 DOI: 10.1145/3115389

R. C. A. Alves, C. Margi

引用次数: 3

Fast Power and Energy Management for Future Many-Core Systems 未来多核系统的快速电源和能源管理

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2017-09-05 DOI: 10.1145/3086504

Yanpei Liu, Guilherme Cox, Qingyuan Deng, S. Draper, R. Bianchini

{"title":"Fast Power and Energy Management for Future Many-Core Systems","authors":"Yanpei Liu, Guilherme Cox, Qingyuan Deng, S. Draper, R. Bianchini","doi":"10.1145/3086504","DOIUrl":"https://doi.org/10.1145/3086504","url":null,"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.","PeriodicalId":105474,"journal":{"name":"ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130587257","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: 6

The Economics of the Cloud 云的经济学

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2017-08-17 DOI: 10.1145/3086574

Jonatha Anselmi, D. Ardagna, John C.S. Lui, A. Wierman, Yunjian Xu, Zichao Yang

引用次数: 62

Controlling the Variability of Capacity Allocations Using Service Deferrals 使用服务延迟控制容量分配的可变性

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2017-08-08 DOI: 10.1145/3086506

Andrés Ferragut, F. Paganini, A. Wierman

引用次数: 4

Insertion of PETSc in the OpenFOAM Framework 在OpenFOAM框架中插入PETSc

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2017-08-08 DOI: 10.1145/3098821

Hao Li, Xinhai Xu, Miao Wang, Chao Li, Xiaoguang Ren, Xuejun Yang

引用次数: 5

On the Convergence of the TTL Approximation for an LRU Cache under Independent Stationary Request Processes 独立平稳请求过程下LRU缓存TTL逼近的收敛性

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2017-07-19 DOI: 10.1145/3239164

Bo Jiang, P. Nain, D. Towsley

引用次数: 31