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