ART and Fuzzy K-means Clustering Based Algorithm for Packet Classification

Author

Qu, Bo ; Gou, Shuiping ; Jiao, Licheng

Author_Institution

Xidian Univ., Xi´´an

fYear

2007

fDate

May 30 2007-June 1 2007

Firstpage

1987

Lastpage

1991

Abstract

Existing algorithms for packet classification always deal with a ready rule set. However, now a day, large classifiers´ rule sets are huger and huger (say, 100 000 rules). Generated these rules by hand is so hard, and causes lots of redundant rules. In this paper, we present a two stage cluster based algorithm for packet classification, which aims to generate filter rules automatically for permitted packets. Based on the scheme, a three-field packet classification for permitted packets (sev-address, sev-port and protocol) is proposed. Experimental results show that the scheme can significantly reduce needed filter rules for permitted packets and the range of IP address lookup.

Keywords

IP networks; fuzzy set theory; pattern classification; pattern clustering; telecommunication network routing; ART clustering algorithm; IP router address lookup; classifiers filter rule sets; fuzzy k-means clustering algorithm; packet classification; Classification algorithms; Clustering algorithms; Filters; Information processing; Network address translation; Protocols; Radar signal processing; Routing; Signal processing algorithms; Subspace constraints; IP address lookup; field; filter rules; packet classification; server IP address;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Automation, 2007. ICCA 2007. IEEE International Conference on

Conference_Location

Guangzhou

Print_ISBN

978-1-4244-0818-4

Electronic_ISBN

978-1-4244-0818-4

Type

conf

DOI

10.1109/ICCA.2007.4376708

Filename

4376708