H. Liu, Xin Wu, Ming Zhang, Lihua Yuan, Roger Wattenhofer, D. Maltz
Datacenter networks (DCNs) are constantly evolving due to various updates such as switch upgrades and VM migrations. Each update must be carefully planned and executed in order to avoid disrupting many of the mission-critical, interactive applications hosted in DCNs. The key challenge arises from the inherent difficulty in synchronizing the changes to many devices, which may result in unforeseen transient link load spikes or even congestions. We present one primitive, zUpdate, to perform congestion-free network updates under asynchronous switch and traffic matrix changes. We formulate the update problem using a network model and apply our model to a variety of representative update scenarios in DCNs. We develop novel techniques to handle several practical challenges in realizing zUpdate as well as implement the zUpdate prototype on OpenFlow switches and deploy it on a testbed that resembles real DCN topology. Our results, from both real-world experiments and large-scale trace-driven simulations, show that zUpdate can effectively perform congestion-free updates in production DCNs.
{"title":"zUpdate: updating data center networks with zero loss","authors":"H. Liu, Xin Wu, Ming Zhang, Lihua Yuan, Roger Wattenhofer, D. Maltz","doi":"10.1145/2486001.2486005","DOIUrl":"https://doi.org/10.1145/2486001.2486005","url":null,"abstract":"Datacenter networks (DCNs) are constantly evolving due to various updates such as switch upgrades and VM migrations. Each update must be carefully planned and executed in order to avoid disrupting many of the mission-critical, interactive applications hosted in DCNs. The key challenge arises from the inherent difficulty in synchronizing the changes to many devices, which may result in unforeseen transient link load spikes or even congestions. We present one primitive, zUpdate, to perform congestion-free network updates under asynchronous switch and traffic matrix changes. We formulate the update problem using a network model and apply our model to a variety of representative update scenarios in DCNs. We develop novel techniques to handle several practical challenges in realizing zUpdate as well as implement the zUpdate prototype on OpenFlow switches and deploy it on a testbed that resembles real DCN topology. Our results, from both real-world experiments and large-scale trace-driven simulations, show that zUpdate can effectively perform congestion-free updates in production DCNs.","PeriodicalId":159374,"journal":{"name":"Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM","volume":"370 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133018516","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}
There is a growing body of research on mechanisms for preserving online user privacy while still allowing aggregate queries over private user data. A common approach is to store user data at users' devices, and to query the data in such a way that a differentially private noisy result is produced without exposing individual user data to any system component. A particular challenge is to design a system that scales well while limiting how much the malicious users can distort the result. This paper presents SplitX, a high-performance analytics system for making differentially private queries over distributed user data. SplitX is typically two to three orders of magnitude more efficient in bandwidth, and from three to five orders of magnitude more efficient in computation than previous comparable systems, while operating under a similar trust model. SplitX accomplishes this performance by replacing public-key operations with exclusive-or operations. This paper presents the design of SplitX, analyzes its security and performance, and describes its implementation and deployment across 416 users.
{"title":"SplitX: high-performance private analytics","authors":"Ruichuan Chen, I. E. Akkus, P. Francis","doi":"10.1145/2486001.2486013","DOIUrl":"https://doi.org/10.1145/2486001.2486013","url":null,"abstract":"There is a growing body of research on mechanisms for preserving online user privacy while still allowing aggregate queries over private user data. A common approach is to store user data at users' devices, and to query the data in such a way that a differentially private noisy result is produced without exposing individual user data to any system component. A particular challenge is to design a system that scales well while limiting how much the malicious users can distort the result. This paper presents SplitX, a high-performance analytics system for making differentially private queries over distributed user data. SplitX is typically two to three orders of magnitude more efficient in bandwidth, and from three to five orders of magnitude more efficient in computation than previous comparable systems, while operating under a similar trust model. SplitX accomplishes this performance by replacing public-key operations with exclusive-or operations. This paper presents the design of SplitX, analyzes its security and performance, and describes its implementation and deployment across 416 users.","PeriodicalId":159374,"journal":{"name":"Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133147665","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}
In this work, we present a distributed caching solution which addresses the problem of efficient delivery of HTTP live streams in large private networks. With our system, we have conducted tests on a number of pilot deployments. The largest of them, with 3000 concurrent viewers, consistently showed that our system saves more than 90% of traffic towards the source of the stream while providing the same quality of user experience of a CDN. Another result is that our solution was able to reduce the load on the bottlenecks in the network by an average of 91.6%.
{"title":"On HTTP live streaming in large enterprises","authors":"Roberto Roverso, Sameh El-Ansary, Mikael Högqvist","doi":"10.1145/2486001.2491685","DOIUrl":"https://doi.org/10.1145/2486001.2491685","url":null,"abstract":"In this work, we present a distributed caching solution which addresses the problem of efficient delivery of HTTP live streams in large private networks. With our system, we have conducted tests on a number of pilot deployments. The largest of them, with 3000 concurrent viewers, consistently showed that our system saves more than 90% of traffic towards the source of the stream while providing the same quality of user experience of a CDN. Another result is that our solution was able to reduce the load on the bottlenecks in the network by an average of 91.6%.","PeriodicalId":159374,"journal":{"name":"Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134490998","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}
Zhongjin Liu, Yong Li, L. Su, Depeng Jin, Lieguang Zeng
A significant concern for cloud operators is to provide global network performance isolation for concurrent tenants. To address this, we propose M2cloud, a software defined framework providing scalable network control for multi-site data centers (DCs). M2cloud employs two-level controllers with decoupled functions, providing each tenant with flexible virtualization support in both intra- and inter-DC networks.
{"title":"M2cloud: software defined multi-site data center network control framework for multi-tenant","authors":"Zhongjin Liu, Yong Li, L. Su, Depeng Jin, Lieguang Zeng","doi":"10.1145/2486001.2491725","DOIUrl":"https://doi.org/10.1145/2486001.2491725","url":null,"abstract":"A significant concern for cloud operators is to provide global network performance isolation for concurrent tenants. To address this, we propose M2cloud, a software defined framework providing scalable network control for multi-site data centers (DCs). M2cloud employs two-level controllers with decoupled functions, providing each tenant with flexible virtualization support in both intra- and inter-DC networks.","PeriodicalId":159374,"journal":{"name":"Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134380933","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}
Sachin Sharma, D. Staessens, D. Colle, M. Pickavet, P. Demeester
RouteFlow provides a way to run routing control platforms (e.g. Quagga) in OpenFlow networks. One of the issues of RouteFlow is that an administrator needs to devote a lot of time (typically 7 hours for 28 switches) in manual configurations. We propose and demonstrate a framework that can automatically configure RouteFlow. For this demonstration, we use an emulated pan-European topology of 28 switches. In the demonstration, we stream a video clip from a server to a remote client, and show that the video clip reaches at the remote client within 4 minutes (including the configuration time). In addition, we show automatic configuration of RouteFlow using a GUI (Graphical User Interface).
{"title":"Automatic configuration of routing control platforms in OpenFlow networks","authors":"Sachin Sharma, D. Staessens, D. Colle, M. Pickavet, P. Demeester","doi":"10.1145/2486001.2491695","DOIUrl":"https://doi.org/10.1145/2486001.2491695","url":null,"abstract":"RouteFlow provides a way to run routing control platforms (e.g. Quagga) in OpenFlow networks. One of the issues of RouteFlow is that an administrator needs to devote a lot of time (typically 7 hours for 28 switches) in manual configurations. We propose and demonstrate a framework that can automatically configure RouteFlow. For this demonstration, we use an emulated pan-European topology of 28 switches. In the demonstration, we stream a video clip from a server to a remote client, and show that the video clip reaches at the remote client within 4 minutes (including the configuration time). In addition, we show automatic configuration of RouteFlow using a GUI (Graphical User Interface).","PeriodicalId":159374,"journal":{"name":"Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115044149","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}
The explosive growth of "big data" is giving rise to a new breed of large scale graph systems, such as Pregel. This poster describes our ongoing work in characterizing and minimizing the communication cost of Bulk Synchronous Parallel (BSP) graph mining systems, like Pregel, when scaling to 4,096 compute nodes. Existing implementations generally assume a fixed communication cost. This is sufficient in small deployments as the BSP programming model (i.e., overlapping computation and communication) masks small variations in the underlying network. In large scale deployments, such variations can dominate the overall runtime characteristics. In this poster, we first quantify the impact of network communication on the total compute time of a Pregel system. We then propose an efficient vertex placement strategy that subsamples highly connected vertices and applies the Reverse Cuthill-McKee (RCM) algorithm to efficiently partition the input graph and place partitions closer to each other based on their expected communication patterns. We finally describe a vertex replication strategy to further reduce communication overhead.
{"title":"To 4,000 compute nodes and beyond: network-aware vertex placement in large-scale graph processing systems","authors":"Karim Awara, H. Jamjoom, Panos Kalnis","doi":"10.1145/2486001.2491726","DOIUrl":"https://doi.org/10.1145/2486001.2491726","url":null,"abstract":"The explosive growth of \"big data\" is giving rise to a new breed of large scale graph systems, such as Pregel. This poster describes our ongoing work in characterizing and minimizing the communication cost of Bulk Synchronous Parallel (BSP) graph mining systems, like Pregel, when scaling to 4,096 compute nodes. Existing implementations generally assume a fixed communication cost. This is sufficient in small deployments as the BSP programming model (i.e., overlapping computation and communication) masks small variations in the underlying network. In large scale deployments, such variations can dominate the overall runtime characteristics. In this poster, we first quantify the impact of network communication on the total compute time of a Pregel system. We then propose an efficient vertex placement strategy that subsamples highly connected vertices and applies the Reverse Cuthill-McKee (RCM) algorithm to efficiently partition the input graph and place partitions closer to each other based on their expected communication patterns. We finally describe a vertex replication strategy to further reduce communication overhead.","PeriodicalId":159374,"journal":{"name":"Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129543158","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}
Z. Qazi, Jeongkeun Lee, Tao Jin, G. Bellala, M. Arndt, G. Noubir
We present a framework, Atlas, which incorporates application-awareness into Software-Defined Networking (SDN), which is currently capable of L2/3/4-based policy enforcement but agnostic to higher layers. Atlas enables fine-grained, accurate and scalable application classification in SDN. It employs a machine learning (ML) based traffic classification technique, a crowd-sourcing approach to obtain ground truth data and leverages SDN's data reporting mechanism and centralized control. We prototype Atlas on HP Labs wireless networks and observe 94% accuracy on average, for top 40 Android applications.
{"title":"Application-awareness in SDN","authors":"Z. Qazi, Jeongkeun Lee, Tao Jin, G. Bellala, M. Arndt, G. Noubir","doi":"10.1145/2486001.2491700","DOIUrl":"https://doi.org/10.1145/2486001.2491700","url":null,"abstract":"We present a framework, Atlas, which incorporates application-awareness into Software-Defined Networking (SDN), which is currently capable of L2/3/4-based policy enforcement but agnostic to higher layers. Atlas enables fine-grained, accurate and scalable application classification in SDN. It employs a machine learning (ML) based traffic classification technique, a crowd-sourcing approach to obtain ground truth data and leverages SDN's data reporting mechanism and centralized control. We prototype Atlas on HP Labs wireless networks and observe 94% accuracy on average, for top 40 Android applications.","PeriodicalId":159374,"journal":{"name":"Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126441761","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}
G'abor R'etv'ari, János Tapolcai, Attila KHorosi, Andr'as Majd'an, Zalán Heszberger
Lately, there has been an upsurge of interest in compressed data structures, aiming to pack ever larger quantities of information into constrained memory without sacrificing the efficiency of standard operations, like random access, search, or update. The main goal of this paper is to demonstrate how data compression can benefit the networking community, by showing how to squeeze the IP Forwarding Information Base (FIB), the giant table consulted by IP routers to make forwarding decisions, into information-theoretical entropy bounds, with essentially zero cost on longest prefix match and FIB update. First, we adopt the state-of-the-art in compressed data structures, yielding a static entropy-compressed FIB representation with asymptotically optimal lookup. Then, we re-design the venerable prefix tree, used commonly for IP lookup for at least 20 years in IP routers, to also admit entropy bounds and support lookup in optimal time and update in nearly optimal time. Evaluations on a Linux kernel prototype indicate that our compressors encode a FIB comprising more than 440K prefixes to just about 100--400 KBytes of memory, with a threefold increase in lookup throughput and no penalty on FIB updates.
{"title":"Compressing IP forwarding tables: towards entropy bounds and beyond","authors":"G'abor R'etv'ari, János Tapolcai, Attila KHorosi, Andr'as Majd'an, Zalán Heszberger","doi":"10.1145/2486001.2486009","DOIUrl":"https://doi.org/10.1145/2486001.2486009","url":null,"abstract":"Lately, there has been an upsurge of interest in compressed data structures, aiming to pack ever larger quantities of information into constrained memory without sacrificing the efficiency of standard operations, like random access, search, or update. The main goal of this paper is to demonstrate how data compression can benefit the networking community, by showing how to squeeze the IP Forwarding Information Base (FIB), the giant table consulted by IP routers to make forwarding decisions, into information-theoretical entropy bounds, with essentially zero cost on longest prefix match and FIB update. First, we adopt the state-of-the-art in compressed data structures, yielding a static entropy-compressed FIB representation with asymptotically optimal lookup. Then, we re-design the venerable prefix tree, used commonly for IP lookup for at least 20 years in IP routers, to also admit entropy bounds and support lookup in optimal time and update in nearly optimal time. Evaluations on a Linux kernel prototype indicate that our compressors encode a FIB comprising more than 440K prefixes to just about 100--400 KBytes of memory, with a threefold increase in lookup throughput and no penalty on FIB updates.","PeriodicalId":159374,"journal":{"name":"Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127726205","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}
With advances of bandwidth-intensive mobile devices (e.g., smart phones, tablet computers), the data traffic for wireless data network has grown tremendously, and is predicted to further increase by more than 10 times in the next five years. The tremendous increase in transmission demand may cause serious congestions. This challenges network operators to find new ways to improve, or at least maintain their service quality. There are many solutions to address this problem from a technical viewpoint [1, 2]. In this paper instead, we try to solve this problem using a pricing approach. The rationales are: 1) traffic demand is highly volatile over time, so it is neither physically easy nor economically profitable to purely rely on technology to meet the extreme demand at peak time; and 2) a large amount of traffic do not have realtime requirement, or are unnecessary at all, and pricing has been proven as an effective way to shape users’ behaviors [3]. Current pricing models are not well suited for wireless applications: flat rate pricing is dominant in broadband network where bandwidth is usually sufficient, but usually causes congestions in wireless environment. For example, WeChat, a very popular mobile social application in China, uses data network to send text, voice and photos. Under the flat rate pricing model today, people often relentlessly upload photos and “short talk” of trivial errands. As a result, ISPs incur
{"title":"The effectiveness of time dependent pricing in controlling usage incentives in wireless data network","authors":"L. Zhang, Weijie Wu, Dan Wang","doi":"10.1145/2486001.2491731","DOIUrl":"https://doi.org/10.1145/2486001.2491731","url":null,"abstract":"With advances of bandwidth-intensive mobile devices (e.g., smart phones, tablet computers), the data traffic for wireless data network has grown tremendously, and is predicted to further increase by more than 10 times in the next five years. The tremendous increase in transmission demand may cause serious congestions. This challenges network operators to find new ways to improve, or at least maintain their service quality. There are many solutions to address this problem from a technical viewpoint [1, 2]. In this paper instead, we try to solve this problem using a pricing approach. The rationales are: 1) traffic demand is highly volatile over time, so it is neither physically easy nor economically profitable to purely rely on technology to meet the extreme demand at peak time; and 2) a large amount of traffic do not have realtime requirement, or are unnecessary at all, and pricing has been proven as an effective way to shape users’ behaviors [3]. Current pricing models are not well suited for wireless applications: flat rate pricing is dominant in broadband network where bandwidth is usually sufficient, but usually causes congestions in wireless environment. For example, WeChat, a very popular mobile social application in China, uses data network to send text, voice and photos. Under the flat rate pricing model today, people often relentlessly upload photos and “short talk” of trivial errands. As a result, ISPs incur","PeriodicalId":159374,"journal":{"name":"Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124027090","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}
RFIDs are emerging as a vital component of the Internet of Things. In 2012, billions of RFIDs have been deployed to locate equipment, track drugs, tag retail goods, etc. Current RFID systems, however, can only identify whether a tagged object is within radio range (which could be up to tens of meters), but cannot pinpoint its exact location. Past proposals for addressing this limitation rely on a line-of-sight model and hence perform poorly when faced with multipath effects or non-line-of-sight, which are typical in real-world deployments. This paper introduces the first fine-grained RFID positioning system that is robust to multipath and non-line-of-sight scenarios. Unlike past work, which considers multipath as detrimental, our design exploits multipath to accurately locate RFIDs. The intuition underlying our design is that nearby RFIDs experience a similar multipath environment (e.g., reflectors in the environment) and thus exhibit similar multipath profiles. We capture and extract these multipath profiles by using a synthetic aperture radar (SAR) created via antenna motion. We then adapt dynamic time warping (DTW) techniques to pinpoint a tag's location. We built a prototype of our design using USRP software radios. Results from a deployment of 200 commercial RFIDs in our university library demonstrate that the new design can locate misplaced books with a median accuracy of 11~cm.
{"title":"Dude, where's my card?: RFID positioning that works with multipath and non-line of sight","authors":"Jue Wang, D. Katabi","doi":"10.1145/2486001.2486029","DOIUrl":"https://doi.org/10.1145/2486001.2486029","url":null,"abstract":"RFIDs are emerging as a vital component of the Internet of Things. In 2012, billions of RFIDs have been deployed to locate equipment, track drugs, tag retail goods, etc. Current RFID systems, however, can only identify whether a tagged object is within radio range (which could be up to tens of meters), but cannot pinpoint its exact location. Past proposals for addressing this limitation rely on a line-of-sight model and hence perform poorly when faced with multipath effects or non-line-of-sight, which are typical in real-world deployments. This paper introduces the first fine-grained RFID positioning system that is robust to multipath and non-line-of-sight scenarios. Unlike past work, which considers multipath as detrimental, our design exploits multipath to accurately locate RFIDs. The intuition underlying our design is that nearby RFIDs experience a similar multipath environment (e.g., reflectors in the environment) and thus exhibit similar multipath profiles. We capture and extract these multipath profiles by using a synthetic aperture radar (SAR) created via antenna motion. We then adapt dynamic time warping (DTW) techniques to pinpoint a tag's location. We built a prototype of our design using USRP software radios. Results from a deployment of 200 commercial RFIDs in our university library demonstrate that the new design can locate misplaced books with a median accuracy of 11~cm.","PeriodicalId":159374,"journal":{"name":"Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121356985","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}
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