ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)最新文献_第7页

Copula Analysis of Temporal Dependence Structure in Markov Modulated Poisson Process and Its Applications 马尔可夫调制泊松过程中时间相关结构的联结分析及其应用

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2017-06-29 DOI: 10.1145/3089254

Fang Dong, Kui Wu, Venkatesh Srinivasan

{"title":"Copula Analysis of Temporal Dependence Structure in Markov Modulated Poisson Process and Its Applications","authors":"Fang Dong, Kui Wu, Venkatesh Srinivasan","doi":"10.1145/3089254","DOIUrl":"https://doi.org/10.1145/3089254","url":null,"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.","PeriodicalId":105474,"journal":{"name":"ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126380629","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: 4

On the Role of Clustering in Personalized PageRank Estimation 聚类在个性化PageRank估计中的作用

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2017-06-04 DOI: 10.1145/3366635

Daniel Vial, V. Subramanian

{"title":"On the Role of Clustering in Personalized PageRank Estimation","authors":"Daniel Vial, V. Subramanian","doi":"10.1145/3366635","DOIUrl":"https://doi.org/10.1145/3366635","url":null,"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. 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.","PeriodicalId":105474,"journal":{"name":"ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123931226","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

Obtaining and Managing Answer Quality for Online Data-Intensive Services 在线数据密集型服务的回答质量获取与管理

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2017-04-26 DOI: 10.1145/3055280

Jaimie Kelley, Christopher Stewart, Nathaniel Morris, Devesh Tiwari, Yuxiong He, S. Elnikety

{"title":"Obtaining and Managing Answer Quality for Online Data-Intensive Services","authors":"Jaimie Kelley, Christopher Stewart, Nathaniel Morris, Devesh Tiwari, Yuxiong He, S. Elnikety","doi":"10.1145/3055280","DOIUrl":"https://doi.org/10.1145/3055280","url":null,"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.","PeriodicalId":105474,"journal":{"name":"ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129068908","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: 16

Advance Reservation Games 提前预订游戏

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2017-04-06 DOI: 10.1145/3053046

Eran Simhon, D. Starobinski

{"title":"Advance Reservation Games","authors":"Eran Simhon, D. Starobinski","doi":"10.1145/3053046","DOIUrl":"https://doi.org/10.1145/3053046","url":null,"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.","PeriodicalId":105474,"journal":{"name":"ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114836379","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: 7

Evaluating the Combined Effect of Memory Capacity and Concurrency for Many-Core Chip Design 多核芯片设计中内存容量和并发性的综合影响评估

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2017-03-06 DOI: 10.1145/3038915

Yuhang Liu, Xian-He Sun

{"title":"Evaluating the Combined Effect of Memory Capacity and Concurrency for Many-Core Chip Design","authors":"Yuhang Liu, Xian-He Sun","doi":"10.1145/3038915","DOIUrl":"https://doi.org/10.1145/3038915","url":null,"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 C2-Bound, a data-driven analytical model that serves the purpose of optimizing many-core design. C2-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 C2-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 C2-Bound, the design space of chip design can be narrowed down significantly up to four orders of magnitude. C2-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.","PeriodicalId":105474,"journal":{"name":"ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133666770","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

Measurement, Modeling, and Analysis of the Mobile App Ecosystem 移动应用生态系统的测量、建模和分析

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2017-03-06 DOI: 10.1145/2993419

Thanasis Petsas, A. Papadogiannakis, M. Polychronakis, E. Markatos, T. Karagiannis

{"title":"Measurement, Modeling, and Analysis of the Mobile App Ecosystem","authors":"Thanasis Petsas, A. Papadogiannakis, M. Polychronakis, E. Markatos, T. Karagiannis","doi":"10.1145/2993419","DOIUrl":"https://doi.org/10.1145/2993419","url":null,"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.","PeriodicalId":105474,"journal":{"name":"ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)","volume":"113 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129101607","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: 22

Detecting Sponsored Recommendations 检测赞助推荐

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2016-11-18 DOI: 10.1145/2988543

Subhashini Krishnasamy, Rajat Sen, S. Shakkottai, Sewoong Oh

{"title":"Detecting Sponsored Recommendations","authors":"Subhashini Krishnasamy, Rajat Sen, S. Shakkottai, Sewoong Oh","doi":"10.1145/2988543","DOIUrl":"https://doi.org/10.1145/2988543","url":null,"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.","PeriodicalId":105474,"journal":{"name":"ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115334362","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

File Dissemination in Dynamic Graphs 动态图形中的文件传播

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2016-11-18 DOI: 10.1145/2981344

P. Nain, D. Towsley

引用次数: 1

Fairness and Incentive Considerations in Energy Apportionment Policies 能源分配政策中的公平与激励因素

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2016-11-01 DOI: 10.1145/2970816

Ekhiotz Jon Vergara, S. Nadjm-Tehrani, Mikael Asplund

{"title":"Fairness and Incentive Considerations in Energy Apportionment Policies","authors":"Ekhiotz Jon Vergara, S. Nadjm-Tehrani, Mikael Asplund","doi":"10.1145/2970816","DOIUrl":"https://doi.org/10.1145/2970816","url":null,"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.","PeriodicalId":105474,"journal":{"name":"ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)","volume":"363 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115901310","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: 5

Self-Similarity in Social Network Dynamics 社会网络动力学中的自相似性

ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS) Pub Date : 2016-10-23 DOI: 10.1145/2994142

Qingyun Liu, Xiaohan Zhao, W. Willinger, Xiao Wang, Ben Y. Zhao, Haitao Zheng

{"title":"Self-Similarity in Social Network Dynamics","authors":"Qingyun Liu, Xiaohan Zhao, W. Willinger, Xiao Wang, Ben Y. Zhao, Haitao Zheng","doi":"10.1145/2994142","DOIUrl":"https://doi.org/10.1145/2994142","url":null,"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.","PeriodicalId":105474,"journal":{"name":"ACM Transactions on Modeling and Performance Evaluation of Computing Systems (TOMPECS)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117144622","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: 11