Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems最新文献

{"title":"Pseudo-Separation for Assessment of Structural Vulnerability of a Network","authors":"Alan Kuhnle, Tianyi Pan, Victoria G. Crawford, M. A. Alim, M. Thai","doi":"10.1145/3078505.3078538","DOIUrl":"https://doi.org/10.1145/3078505.3078538","url":null,"abstract":"Based upon the idea that network functionality is impaired if two nodes in a network are sufficiently separated in terms of a given metric, we introduce two combinatorial pseudocut problems generalizing the classical min-cut and multi-cut problems. We expect the pseudocut problems will find broad relevance to the study of network reliability. We comprehensively analyze the computational complexity of the pseudocut problems and provide three approximation algorithms for these problems. Motivated by applications in communication networks with strict Quality-of-Service (QoS) requirements, we demonstrate the utility of the pseudocut problems by proposing a targeted vulnerability assessment for the structure of communication networks using QoS metrics; we perform experimental evaluations of our proposed approximation algorithms in this context.","PeriodicalId":133673,"journal":{"name":"Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117308271","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}

{"title":"On Optimal Two-Sided Pricing of Congested Networks","authors":"Xin Wang, Richard T. B. Ma, Yinlong Xu","doi":"10.1145/3078505.3078588","DOIUrl":"https://doi.org/10.1145/3078505.3078588","url":null,"abstract":"Internet Access Providers (APs) have built massive network platforms by which end-users and Content Providers (CPs) can connect and transmit data to each other. Traditionally, APs adopt one-sided pricing schemes and obtain revenues mainly from end-users. With the fast development of data-intensive services, e.g., online video streaming and cloud-based applications, Internet traffic has been growing rapidly. To sustain the traffic growth and enhance user experiences, APs have to upgrade network infrastructures and expand capacities; however, they feel that the revenues from end-users are insufficient to recoup the corresponding costs. Consequently, some APs, e.g., Comcast and AT&T, have recently shifted towards two-sided pricing schemes, i.e., they start to impose termination fees on CPs' data traffic in addition to charging end-users. Although some previous work has studied the economics of two-sided pricing in network markets, network congestion and its impacts on the utilities of different parties were often overlooked. However, the explosive traffic growth has caused severe congestion in many regional and global networks, especially during peak hours, which degrades end-users' experiences and reduces their data demand. This will strongly affect the profits of APs and the utilities of end-users and CPs. For optimizing individual and social utilities, APs and regulators need to reflect the design of pricing strategies and regulatory policies accordingly. So far, little is known about 1) the optimal two-sided pricing structure in a congested network and its changes under varying network environments, e.g., capacities of APs and congestion sensitivities of users, and 2) potential regulations on two-sided pricing for protecting social welfare from monopolistic providers. To address these questions, one challenge is to accurately capture endogenous congestion in networks. Although the level of congestion is influenced by network throughput, the users' traffic demand and throughput are also influenced by network congestion. It is crucial to capture this endogenous congestion so as to faithfully characterize the impacts of two-sided pricing in congested networks. In this work, we propose a novel model of a two-sided congested network built by an AP. We model network congestion as a function of AP's capacity and network throughput, which is also a function of the congestion level. We use different forms of the functions to capture congestion metric based on different service models, e.g., M/M/1 queue or capacity sharing, and user traffic based on different data types, e.g., online video or text. We characterize users' population and traffic demand under pricing and congestion parameters and derive an endogenous system congestion under an equilibrium. Based on the equilibrium model, we explore the structures of two-sided pricing which optimize the AP's profit and social welfare. We analyze the sensitivities of the optimal pricing under varying model par","PeriodicalId":133673,"journal":{"name":"Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128935698","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}

{"title":"Security Game with Non-additive Utilities and Multiple Attacker Resources","authors":"Sinong Wang, N. Shroff","doi":"10.1145/3078505.3078519","DOIUrl":"https://doi.org/10.1145/3078505.3078519","url":null,"abstract":"There has been significant interest in studying security games for modeling the interplay of attacks and defenses on various systems involving critical infrastructure, financial system security, political campaigns, and civil safeguarding. However, existing security game models typically either assume additive utility functions, or that the attacker can attack only one target. Such assumptions lead to tractable analysis, but miss key inherent dependencies that exist among different targets in current complex networks. In this paper, we generalize the classical security game models to allow for non-additive utility functions. We also allow attackers to be able to attack multiple targets. We examine such a general security game from a theoretical perspective and provide a unified view. In particular, we show that each security game is equivalent to a combinatorial optimization problem over a set system ε, which consists of defender's pure strategy space. The key technique we use is based on the transformation, projection of a polytope, and the ellipsoid method. This work settles several open questions in security game domain and extends the state-of-the-art of both the polynomial solvable and NP-hard class of the security game.","PeriodicalId":133673,"journal":{"name":"Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128751788","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}

{"title":"Overcommitment in Cloud Services Bin packing with Chance Constraints","authors":"Maxime C. Cohen, Philipp W. Keller, V. Mirrokni, Morteza Zadimoghaddam","doi":"10.2139/ssrn.2822188","DOIUrl":"https://doi.org/10.2139/ssrn.2822188","url":null,"abstract":"This paper considers a traditional problem of resource allocation, scheduling jobs on machines. One such recent application is cloud computing, where jobs arrive in an online fashion with capacity requirements and need to be immediately scheduled on physical machines in data centers. It is often observed that the requested capacities are not fully utilized, hence offering an opportunity to employ an overcommitment policy, i.e., selling resources beyond capacity. Setting the right overcommitment level can induce a significant cost reduction for the cloud provider, while only inducing a very low risk of violating capacity constraints. We introduce and study a model that quantifies the value of overcommitment by modeling the problem as a bin packing with chance constraints. We then propose an alternative formulation that transforms each chance constraint into a submodular function. We show that our model captures the risk pooling effect and can guide scheduling and overcommitment decisions. We also develop a family of online algorithms that are intuitive, easy to implement and provide a constant factor guarantee from optimal. Finally, we calibrate our model using realistic workload data, and test our approach in a practical setting. Our analysis and experiments illustrate the benefit of overcommitment in cloud services, and suggest a cost reduction of 1.5% to 17% depending on the provider's risk tolerance.","PeriodicalId":133673,"journal":{"name":"Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128766913","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}

{"title":"Quality and Cost of Deterministic Network Calculus: Design and Evaluation of an Accurate and Fast Analysis","authors":"Steffen Bondorf, Paul Nikolaus, J. Schmitt","doi":"10.1145/3078505.3078594","DOIUrl":"https://doi.org/10.1145/3078505.3078594","url":null,"abstract":"Networks are integral parts of modern safety-critical systems and certification demands the provision of guarantees for data transmissions. Deterministic Network Calculus (DNC) can compute a worst-case bound on a data flow's end-to-end delay. Accuracy of DNC results has been improved steadily, resulting in two DNC branches: the classical algebraic analysis (algDNC) and the more recent optimization-based analysis (optDNC). The optimization-based branch provides a theoretical solution for tight bounds. Its computational cost grows, however, (possibly super-)exponentially with the network size. Consequently, a heuristic optimization formulation trading accuracy against computational costs was proposed. In this paper, we challenge optimization-based DNC with a novel algebraic DNC algorithm. We show that: (1) no current optimization formulation scales well with the network size and (2) algebraic DNC can be considerably improved in both aspects, accuracy and computational cost. To that end, we contribute a novel DNC algorithm that transfers the optimization's search for best attainable delay bounds to algebraic DNC. It achieves a high degree of accuracy and our novel efficiency improvements reduce the cost of the analysis dramatically. In extensive numerical experiments, we observe that our delay bounds deviate from the optimization-based ones by only 1.142% on average while computation times simultaneously decrease by several orders of magnitude.","PeriodicalId":133673,"journal":{"name":"Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124553811","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}

{"title":"Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems","authors":"B. Hajek, Sewoong Oh, A. Chaintreau, L. Golubchik, Zhi-Li Zhang","doi":"10.1145/3078505","DOIUrl":"https://doi.org/10.1145/3078505","url":null,"abstract":"Welcome to SIGMETRICS 2007! This year's annual ACM SIGMETRICS conference is being held this year in conjunction with the Federated Computing Research Conference (FCRC). The scope of SIGMETRICS encompasses the development and application of state-of-the-art, broadly-applicable analytic, simulation, and measurement-based performance evaluation techniques. In soliciting papers for this year's program, and in selecting members of the Technical Program Committee (TPC), we made a special effort to maintain a breadth of topic coverage. Application areas represented include: distributed systems, networking, multimedia, storage systems, operating system, web services, supercomputing, compilers, architecture, and more. Analytical techniques represented include: scheduling theory, queueing theory, stochastic modeling, high-dimensional geometry, matrix analytic methods, transient time-varying behaviors, competitive ratio analysis, and more. \u0000 \u0000The conference received 179 submissions. We accepted 29 full papers and 19 poster papers. We followed a double-blind reviewing process, and each paper was reviewed by at least three members of the TPC. In some cases additional reviews were sought from specialists outside the TPC. The TPC consisted of 54 members from 8 countries. After extensive email discussions among the whole TPC, the final paper selection was made during a 2-day meeting held at Columbia University on January 26-27, 2007, which was attended by 35 of the PC members, the two program co-chairs, and the general chair. The quality of submissions was quite high and, as a result, the selected papers make up a very strong program, which we hope you will enjoy. \u0000 \u0000After the TPC meeting, a subcommittee selected the best paper award winners. The Best Paper award goes to, \"Modeling the relative fitness of storage,\" by Michael Mesnier, Matthew Wachs, Raja R. Sambasivan, Alice Zheng, and Gregory R. Ganger. The Kenneth C. Sevcik Outstanding Student Paper award goes to, \"An Analysis of Latent Sector Errors in Disk Drives,\" by Lakshmi Bairavasundaram, Garth Goodson, Shankar Pasupathy, and Jiri Schindler.","PeriodicalId":133673,"journal":{"name":"Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122078406","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}