Tianzhu Zhang, Leonardo Linguaglossa, Massimo Gallo, P. Giaccone, D. Rossi
{"title":"FlowMon-DPDK: Parsimonious Per-Flow Software Monitoring at Line Rate","authors":"Tianzhu Zhang, Leonardo Linguaglossa, Massimo Gallo, P. Giaccone, D. Rossi","doi":"10.23919/TMA.2018.8506565","DOIUrl":null,"url":null,"abstract":"Testing experimental network devices requires deep performance analysis, which is usually performed with expensive, not flexible, hardware equipment. With the advent of highspeed packet I/O frameworks, general purpose equipments have narrowed the performance gap in respect of dedicated hardware and a variety of software-based solutions have emerged for handling traffic at very high speed. While the literature abounds with software traffic generators, existing monitoring solutions do not target worst-case scenarios (i.e., 64B packets at line rate) that are particularly relevant for stress-testing high-speed network functions, or occupy too many resources. In this paper we first analyse the design space for high-speed traffic monitoring that leads us to specific choices characterizing FlowMon-DPDK, a DPDK-based software traffic monitor that we release as an open source project. In a nutshell, FlowMon-DPDK provides tunable fine-grained statistics at both packet and flow levels. Experimental results demonstrate that our traffic monitor is able to provide per-flow statistics with 5-nines precision at high-speed (14.88 Mpps) using an exiguous amount of resources. Finally, we showcase FlowMon-DPDK usage by testing two open source prototypes for stateful flow-level end-host and in-network packet processing.","PeriodicalId":6607,"journal":{"name":"2018 Network Traffic Measurement and Analysis Conference (TMA)","volume":"159 s1","pages":"1-8"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Network Traffic Measurement and Analysis Conference (TMA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/TMA.2018.8506565","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16
Abstract
Testing experimental network devices requires deep performance analysis, which is usually performed with expensive, not flexible, hardware equipment. With the advent of highspeed packet I/O frameworks, general purpose equipments have narrowed the performance gap in respect of dedicated hardware and a variety of software-based solutions have emerged for handling traffic at very high speed. While the literature abounds with software traffic generators, existing monitoring solutions do not target worst-case scenarios (i.e., 64B packets at line rate) that are particularly relevant for stress-testing high-speed network functions, or occupy too many resources. In this paper we first analyse the design space for high-speed traffic monitoring that leads us to specific choices characterizing FlowMon-DPDK, a DPDK-based software traffic monitor that we release as an open source project. In a nutshell, FlowMon-DPDK provides tunable fine-grained statistics at both packet and flow levels. Experimental results demonstrate that our traffic monitor is able to provide per-flow statistics with 5-nines precision at high-speed (14.88 Mpps) using an exiguous amount of resources. Finally, we showcase FlowMon-DPDK usage by testing two open source prototypes for stateful flow-level end-host and in-network packet processing.