NDLI: Data stream mining based real-time highspeed traffic classification

Content Provider	IEEE Xplore Digital Library
Author	Guo Mingliang Huang Xiaohong Tian Xu Ma Yan Wang Zhenhua
Copyright Year	2009
Description	Author affiliation: Information Network Center, Research Institute of Networking Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China (Guo Mingliang; Huang Xiaohong; Tian Xu; Ma Yan; Wang Zhenhua)
Abstract	In current high-speed network, Peer-to-Peer(P2P) applications have overtaken Web applications as the major contribution on the Internet. Thereby, how to identify P2P traffic in real-time accurately and efficiently is a key step for network management. In this paper, we highlight the importance of applying data stream method in traffic classification to achieve real-time P2P traffic identification. We not only introduce a VFDT-based real-time highspeed traffic classification method, but also take thoroughly analysis on how to select a reasonable tie confidence (TieC), minimum gathering flow (MinGF) and category number (CaNum). Meanwhile, analysis has been done to ascertain the packet's interval which is used to calculate flow's real-time attribute. Experiment results have shown that when TieC is less than threshold, the larger TieC is, the better accuracy of identification is; when TieC exceeds threshold, decision trees are the same. Concerning MinGF and CaNum, although the smaller both of them are, the better performance of decision tree is, the value of them must be properly set according to requirements of classification system.
Starting Page	700
Ending Page	705
File Size	130599
Page Count	6
File Format	PDF
ISBN	9781424445905
DOI	10.1109/ICBNMT.2009.5347837
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-18
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Laboratories Real-time Telecommunication traffic VFDT Traffic classification Data mining Application software Intelligent networks Data stream High-speed networks Machine learning High speed Streaming media Decision trees IP networks
Content Type	Text
Resource Type	Article

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