Composite lightweight traffic classification system for network management

• Published in: International journal of network management 2010-03, Vol.20 (2), p.85-105
• Main Authors: Li, Jun, Zhang, Shunyi, Li, Cuilian, Yan, Junrong
• Format: Article
• Language: English
• Subjects: Classification; Internet; Lightweight; Management; Networks; Traffic engineering; Traffic flow; Weight reduction
• ISSN: 1055-7148; 1099-1190
• DOI: 10.1002/nem.735

Accurate and real‐time classification of network traffic is significant to a number of network operation and management tasks such as quality of service differentiation, traffic shaping and security surveillance. However, with emerging P2P applications using dynamic port numbers, IP masquerading techniques and payload encryption, accurate and intelligent traffic classification continues to be a big challenge despite a wide range of research work on the topic. Since each classification method has its disadvantages and hardly could meet the specific requirement of Internet traffic classification, this paper innovatively presents a composite traffic classification system. The proposed lightweight system can accurately and effectively identify Internet traffic with good scalability to accommodate both known and unknown/encrypted applications. Furthermore, It promises to satisfy various Internet uses and is feasible for use in real‐time line speed applications. Our experimental results show the distinct advantages of the proposed classification system. Copyright © 2009 John Wiley & Sons, Ltd. Accurate and real‐time classification of network traffic is significant to a number of network operation and management tasks such as quality of service differentiation, traffic shaping and security surveillance. However, with emerging P2P applications using dynamic port numbers, IP masquerading techniques, and payload encryption, accurate and intelligent traffic classification continues to be a big challenge despite a wide range of research work on the topic. Since each classification method has its disadvantages and hardly could meet the specific requirement of Internet traffic classification, this paper innovatively presents a composite traffic classification system, which mainly consists of coarse‐grained classification phase and fine‐grained classification phase. In the coarse‐grained classification phase, traffic is classified into broad categories, whereas in the fine‐grained classification phase, the traffic is further categorized into distinct application types. The proposed lightweight system can accurately and effectively identify Internet traffic with good scalability to accommodate both known and unknown/encrypted applications. Furthermore, It promises to satisfy various Internet uses and is feasible for use in real‐time line speed application. Our experimental results show the distinct advantages of the proposed classification system.