Xiaoban Wu, Yan Luo, Jeronimo Bezerra, Liang-Min Wang
{"title":"Ares: A Scalable High-Performance Passive Measurement Tool Using a Multicore System","authors":"Xiaoban Wu, Yan Luo, Jeronimo Bezerra, Liang-Min Wang","doi":"10.1109/NAS.2019.8834734","DOIUrl":null,"url":null,"abstract":"Network measurement tools must support the collection of fine-grain flow statistics and scale well to the increasing line rates. However, conventional network measurement software tools are inadequate in high-speed network at the current scale. In this paper, we present Ares, a scalable high-performance passive network measurement tool to collect accurate per-flow metrics. Ares is built on a multicore platform, consisting of an effective hierarchical core assignment strategy, an efficient hash table for keeping flow statistics, a novel lockless flow statistics management scheme, as well as cache friendly prefetching. Our extensive performance evaluation shows that Ares brings about 19x speedup for 64-byte packets over existing approaches and can sustain up to a line rate of 100Gbps, while delivering the same level of fine-grained flow metrics.","PeriodicalId":230796,"journal":{"name":"2019 IEEE International Conference on Networking, Architecture and Storage (NAS)","volume":"453 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Conference on Networking, Architecture and Storage (NAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAS.2019.8834734","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Network measurement tools must support the collection of fine-grain flow statistics and scale well to the increasing line rates. However, conventional network measurement software tools are inadequate in high-speed network at the current scale. In this paper, we present Ares, a scalable high-performance passive network measurement tool to collect accurate per-flow metrics. Ares is built on a multicore platform, consisting of an effective hierarchical core assignment strategy, an efficient hash table for keeping flow statistics, a novel lockless flow statistics management scheme, as well as cache friendly prefetching. Our extensive performance evaluation shows that Ares brings about 19x speedup for 64-byte packets over existing approaches and can sustain up to a line rate of 100Gbps, while delivering the same level of fine-grained flow metrics.