DocumentCode :
3098003
Title :
Accurate Traffic Classification with Multi-threaded Processors
Author :
Liu, Yizhen ; Xu, Daxiong ; Sun, Lingge ; Liu, Dong
Author_Institution :
Opt. Commun. & Optoelectron. Inst., Beijing Univ. of Posts & Telecommun., Beijing
fYear :
2008
fDate :
21-22 Dec. 2008
Firstpage :
478
Lastpage :
481
Abstract :
Nowadays traffic classification is a fundamental process for Internet traffic management devices and Internet applications need accurate, high performance and scalable traffic classification. Traditional traffic classification is inaccurate and elementary because they are based on imprecise transport layer port method and have unacceptably memory access latency in packet processing. In this paper, we discuss an accurate multi-stage traffic classification in gigabits Internet traffic management systems using multi-threaded processor. Firstly, we address the problem of inaccurate packet classification and analyze payload of applications and standard protocols. Secondly, we present a multi-stage traffic classification using packet header fields and payload string. Finally, we present the software pipeline architecture and hardware design for our approach with network processor. We used our approach to monitor a carrier´s backbone node for a month. Compared with traditional methods, the multi-stage traffic classification has 91% accuracy in a real network environment.
Keywords :
Internet; multi-threading; pattern classification; pipeline processing; software architecture; telecommunication traffic; Internet traffic management systems; memory access latency; multi stage traffic classification; multi threaded processors; network processor; packet header fields; packet processing; payload string; software pipeline architecture; Access protocols; Application software; Computer architecture; Delay; Hardware; Internet; Monitoring; Payloads; Pipelines; Telecommunication traffic; Internet protocol; multi-threaded; network processor; traffic classification; traffic management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Knowledge Acquisition and Modeling Workshop, 2008. KAM Workshop 2008. IEEE International Symposium on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-3530-2
Electronic_ISBN :
978-1-4244-3531-9
Type :
conf
DOI :
10.1109/KAMW.2008.4810528
Filename :
4810528
Link To Document :
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