{"title":"基于形状汇总统计的实用被动共享瓶颈检测","authors":"D. Hayes, Simone Ferlin Oliveira, M. Welzl","doi":"10.1109/LCN.2014.6925767","DOIUrl":null,"url":null,"abstract":"Practical shared bottleneck detection has proved to be a difficult problem. We present a novel passive approach using efficient estimates of time and frequency domain summary statistics. The approach is not CPU nor network intensive, and has numerous potential applications in the Internet. Simulations and tests over the Internet and 3G cellular network show its efficacy in grouping flows correctly.","PeriodicalId":143262,"journal":{"name":"39th Annual IEEE Conference on Local Computer Networks","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":"{\"title\":\"Practical passive shared bottleneck detection using shape summary statistics\",\"authors\":\"D. Hayes, Simone Ferlin Oliveira, M. Welzl\",\"doi\":\"10.1109/LCN.2014.6925767\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Practical shared bottleneck detection has proved to be a difficult problem. We present a novel passive approach using efficient estimates of time and frequency domain summary statistics. The approach is not CPU nor network intensive, and has numerous potential applications in the Internet. Simulations and tests over the Internet and 3G cellular network show its efficacy in grouping flows correctly.\",\"PeriodicalId\":143262,\"journal\":{\"name\":\"39th Annual IEEE Conference on Local Computer Networks\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"23\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"39th Annual IEEE Conference on Local Computer Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/LCN.2014.6925767\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"39th Annual IEEE Conference on Local Computer Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LCN.2014.6925767","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Practical passive shared bottleneck detection using shape summary statistics
Practical shared bottleneck detection has proved to be a difficult problem. We present a novel passive approach using efficient estimates of time and frequency domain summary statistics. The approach is not CPU nor network intensive, and has numerous potential applications in the Internet. Simulations and tests over the Internet and 3G cellular network show its efficacy in grouping flows correctly.