Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication最新文献_第2页

Low Latency Geo-distributed Data Analytics 低延迟地理分布式数据分析

Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication Pub Date : 2015-08-17 DOI: 10.1145/2785956.2787505

Qifan Pu, G. Ananthanarayanan, P. Bodík, Srikanth Kandula, Aditya Akella, P. Bahl, I. Stoica

{"title":"Low Latency Geo-distributed Data Analytics","authors":"Qifan Pu, G. Ananthanarayanan, P. Bodík, Srikanth Kandula, Aditya Akella, P. Bahl, I. Stoica","doi":"10.1145/2785956.2787505","DOIUrl":"https://doi.org/10.1145/2785956.2787505","url":null,"abstract":"Low latency analytics on geographically distributed datasets (across datacenters, edge clusters) is an upcoming and increasingly important challenge. The dominant approach of aggregating all the data to a single datacenter significantly inflates the timeliness of analytics. At the same time, running queries over geo-distributed inputs using the current intra-DC analytics frameworks also leads to high query response times because these frameworks cannot cope with the relatively low and variable capacity of WAN links. We present Iridium, a system for low latency geo-distributed analytics. Iridium achieves low query response times by optimizing placement of both data and tasks of the queries. The joint data and task placement optimization, however, is intractable. Therefore, Iridium uses an online heuristic to redistribute datasets among the sites prior to queries' arrivals, and places the tasks to reduce network bottlenecks during the query's execution. Finally, it also contains a knob to budget WAN usage. Evaluation across eight worldwide EC2 regions using production queries show that Iridium speeds up queries by 3× -- 19× and lowers WAN usage by 15% -- 64% compared to existing baselines.","PeriodicalId":268472,"journal":{"name":"Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123557404","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: 328

i-tee: A fully automated Cyber Defense Competition for Students i-tee:学生全自动网络防御竞赛

Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication Pub Date : 2015-08-17 DOI: 10.1145/2785956.2790033

M. Ernits, Johannes Tammekänd, O. Maennel

引用次数: 12

Silo: Predictable Message Latency in the Cloud 筒仓:云中可预测的消息延迟

Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication Pub Date : 2015-08-17 DOI: 10.1145/2785956.2787479

K. Jang, Justine Sherry, Hitesh Ballani, Toby Moncaster

引用次数: 158

Enabling Performance Evaluation Beyond 10 Gbps 启用超过10gbps的性能评估

Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication Pub Date : 2015-08-17 DOI: 10.1145/2785956.2790036

G. Antichi, Charalampos Rotsos, A. Moore

{"title":"Enabling Performance Evaluation Beyond 10 Gbps","authors":"G. Antichi, Charalampos Rotsos, A. Moore","doi":"10.1145/2785956.2790036","DOIUrl":"https://doi.org/10.1145/2785956.2790036","url":null,"abstract":"Despite network monitoring and testing being critical for computer networks, current solutions are both extremely expensive and inflexible. This demo presents OSNT (www.osnt.org), a community-driven, high-performance, open-source traffic generator and capture system built on top of the NetFPGA-10G board which enables flexible network testing. The platform supports full line-rate traffic generation regardless of packet size across the four card ports, packet capture filtering and packet thinning in hardware and sub-msec time precision in traffic generation and capture, corrected using an external GPS device. Furthermore, it provides a software APIs to test the dataplane performance of multi-10G switches, providing a starting point for a number of different test cases. OSNT flexibility is further demonstrated through the OFLOPS-turbo platform: an integration of OSNT with the OFLOPS OpenFlow switch performance evaluation platform, enabling control and data plane evaluation of 10G switches. This demo showcases the applicability of the OSNT platform to evaluate the performance of legacy and OpenFlow-enabled networking devices, and demonstrates it using commercial switches.","PeriodicalId":268472,"journal":{"name":"Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127119419","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

Jupiter Rising: A Decade of Clos Topologies and Centralized Control in Google's Datacenter Network 《木星升起:b谷歌数据中心网络的近十年拓扑和集中控制》

Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication Pub Date : 2015-08-17 DOI: 10.1145/2785956.2787508

Arjun Singh, J. Ong, Amit Agarwal, Glen Anderson, Ashby Armistead, Roy Bannon, Seb Boving, Gaurav Desai, Bob Felderman, Paulie Germano, Anand Kanagala, Hong Liu, Jeff Provost, Jason Simmons, Eiichi Tanda, Jim Wanderer, Urs Hölzle, Stephen Stuart, Amin Vahdat

{"title":"Jupiter Rising: A Decade of Clos Topologies and Centralized Control in Google's Datacenter Network","authors":"Arjun Singh, J. Ong, Amit Agarwal, Glen Anderson, Ashby Armistead, Roy Bannon, Seb Boving, Gaurav Desai, Bob Felderman, Paulie Germano, Anand Kanagala, Hong Liu, Jeff Provost, Jason Simmons, Eiichi Tanda, Jim Wanderer, Urs Hölzle, Stephen Stuart, Amin Vahdat","doi":"10.1145/2785956.2787508","DOIUrl":"https://doi.org/10.1145/2785956.2787508","url":null,"abstract":"We present our approach for overcoming the cost, operational complexity, and limited scale endemic to datacenter networks a decade ago. Three themes unify the five generations of datacenter networks detailed in this paper. First, multi-stage Clos topologies built from commodity switch silicon can support cost-effective deployment of building-scale networks. Second, much of the general, but complex, decentralized network routing and management protocols supporting arbitrary deployment scenarios were overkill for single-operator, pre-planned datacenter networks. We built a centralized control mechanism based on a global configuration pushed to all datacenter switches. Third, modular hardware design coupled with simple, robust software allowed our design to also support inter-cluster and wide-area networks. Our datacenter networks run at dozens of sites across the planet, scaling in capacity by 100x over ten years to more than 1Pbps of bisection bandwidth.","PeriodicalId":268472,"journal":{"name":"Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication","volume":"486 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130734950","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: 727

On the Optimization of Request Routing for Content Delivery 内容分发请求路由的优化研究

Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication Pub Date : 2015-08-17 DOI: 10.1145/2785956.2790016

W. Benchaita, S. Ghamri-Doudane, S. Tixeuil

引用次数: 4

Session details: Wireless 会议详情:无线

Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication Pub Date : 2015-08-17 DOI: 10.1145/3261003

K. Jamieson

引用次数: 0

Session details: CDN and Wide Area Infrastructure 会话详细信息:CDN和广域基础设施

Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication Pub Date : 2015-08-17 DOI: 10.1145/3261004

Aditya Akella

引用次数: 0

RPKI MIRO: Monitoring and Inspection of RPKI Objects RPKI MIRO: RPKI对象的监控和检查

Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication Pub Date : 2015-08-17 DOI: 10.1145/2785956.2790026

A. Reuter, Matthias Wählisch, T. Schmidt

引用次数: 7

Packet-Level Telemetry in Large Datacenter Networks 大型数据中心网络中的数据包级遥测

Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication Pub Date : 2015-08-17 DOI: 10.1145/2785956.2787483

Yibo Zhu, Nanxi Kang, Jiaxin Cao, A. Greenberg, Guohan Lu, Ratul Mahajan, D. Maltz, Lihua Yuan, Ming Zhang, Ben Y. Zhao, Haitao Zheng

{"title":"Packet-Level Telemetry in Large Datacenter Networks","authors":"Yibo Zhu, Nanxi Kang, Jiaxin Cao, A. Greenberg, Guohan Lu, Ratul Mahajan, D. Maltz, Lihua Yuan, Ming Zhang, Ben Y. Zhao, Haitao Zheng","doi":"10.1145/2785956.2787483","DOIUrl":"https://doi.org/10.1145/2785956.2787483","url":null,"abstract":"Debugging faults in complex networks often requires capturing and analyzing traffic at the packet level. In this task, datacenter networks (DCNs) present unique challenges with their scale, traffic volume, and diversity of faults. To troubleshoot faults in a timely manner, DCN administrators must a) identify affected packets inside large volume of traffic; b) track them across multiple network components; c) analyze traffic traces for fault patterns; and d) test or confirm potential causes. To our knowledge, no tool today can achieve both the specificity and scale required for this task. We present Everflow, a packet-level network telemetry system for large DCNs. Everflow traces specific packets by implementing a powerful packet filter on top of \"match and mirror\" functionality of commodity switches. It shuffles captured packets to multiple analysis servers using load balancers built on switch ASICs, and it sends \"guided probes\" to test or confirm potential faults. We present experiments that demonstrate Everflow's scalability, and share experiences of troubleshooting network faults gathered from running it for over 6 months in Microsoft's DCNs.","PeriodicalId":268472,"journal":{"name":"Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125565639","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: 287