{"title":"Tracking per-flow state — Binned Duration Flow Tracking","authors":"B. Whitehead, Chung-Horng Lung, P. Rabinovitch","doi":"10.4304/jnw.7.1.37-51","DOIUrl":"https://doi.org/10.4304/jnw.7.1.37-51","url":null,"abstract":"Recent advances in network monitoring have increasingly focused on obtaining per-flow information, such as flow state. Tracking the state of network flows opens up a new dimension of information gathering for network operators, allowing previously unattainable data to be captured. This paper presents a time efficient novel method — Binned Duration Flow Tracking (BDFT) — of tracking per-flow state by grouping valid flows into “bins”. BDFT is intended for high-speed routers where CPU time is crucial. BDFT is time efficient by adopting Bloom filters as the primary data structures. Simulation results show that BDFT can achieve over 99% accuracy on traces of real network traffic.","PeriodicalId":426447,"journal":{"name":"Proceedings of the 2010 International Symposium on Performance Evaluation of Computer and Telecommunication Systems (SPECTS '10)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114679039","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}