{"title":"数据中心的多资源感知拥塞控制","authors":"Deke Guo, Q. Wu, Shanshan Li, Yusong Tan, Quanyuan Wu","doi":"10.1109/ICPADS.2013.119","DOIUrl":null,"url":null,"abstract":"Network has been widely reported as a bottleneck of data center applications. However, current researches of congestion control are unaware of multiple resources consuming and decrease all flows when congestion, ignoring some involved flows may not be the faults. In this paper, we propose a novel multi-resources aware congestion control framework MRTCP to provide a fine-grain control on flows when congestions appear. MRTCP exploits a multi-tuple vector model to measure multi-resources provision and consumption, and develops a novel metric RB (Resource Balance) to denote the heterogeneous amounts of resources employed by each flow. It analyzes which resources are being the bottlenecks that lead to congestions, calculates the responsibility of each flow to this congestion, and then adjusts their sending rates respectively. Our experiment results demonstrate that MRTCP is able to optimize network multi-resources utilization and improve network throughput without adding obvious packets delays.","PeriodicalId":160979,"journal":{"name":"2013 International Conference on Parallel and Distributed Systems","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Multi-resource Aware Congestion Control in Data Centers\",\"authors\":\"Deke Guo, Q. Wu, Shanshan Li, Yusong Tan, Quanyuan Wu\",\"doi\":\"10.1109/ICPADS.2013.119\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Network has been widely reported as a bottleneck of data center applications. However, current researches of congestion control are unaware of multiple resources consuming and decrease all flows when congestion, ignoring some involved flows may not be the faults. In this paper, we propose a novel multi-resources aware congestion control framework MRTCP to provide a fine-grain control on flows when congestions appear. MRTCP exploits a multi-tuple vector model to measure multi-resources provision and consumption, and develops a novel metric RB (Resource Balance) to denote the heterogeneous amounts of resources employed by each flow. It analyzes which resources are being the bottlenecks that lead to congestions, calculates the responsibility of each flow to this congestion, and then adjusts their sending rates respectively. Our experiment results demonstrate that MRTCP is able to optimize network multi-resources utilization and improve network throughput without adding obvious packets delays.\",\"PeriodicalId\":160979,\"journal\":{\"name\":\"2013 International Conference on Parallel and Distributed Systems\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Parallel and Distributed Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPADS.2013.119\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Parallel and Distributed Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPADS.2013.119","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-resource Aware Congestion Control in Data Centers
Network has been widely reported as a bottleneck of data center applications. However, current researches of congestion control are unaware of multiple resources consuming and decrease all flows when congestion, ignoring some involved flows may not be the faults. In this paper, we propose a novel multi-resources aware congestion control framework MRTCP to provide a fine-grain control on flows when congestions appear. MRTCP exploits a multi-tuple vector model to measure multi-resources provision and consumption, and develops a novel metric RB (Resource Balance) to denote the heterogeneous amounts of resources employed by each flow. It analyzes which resources are being the bottlenecks that lead to congestions, calculates the responsibility of each flow to this congestion, and then adjusts their sending rates respectively. Our experiment results demonstrate that MRTCP is able to optimize network multi-resources utilization and improve network throughput without adding obvious packets delays.