Recurrence based nonlinear analysis for network application traffic
Jing YUAN1,2,Junsong WANG1,3,Qiang LI1,Xi CHEN1()
1. Department of Automation, Tsinghua University, Beijing 100084, China 2. National Computer Network Emergency Response Technical Team Coordination Center of China, Beijing 100029, China 3. School of Biomedical Engineering, Tianjin Medical University, Tianjin 300070, China
Accurate characterization of the traffic from different network applications plays an important role in traffic classifications to guarantee the quality of service of Internet traffic. The behavior of various network application traffic was analyzed based on the recurrence properties of the network traffic. A high-dimensional phase space is constructed for the traffic time series and then recurrences in the traffic state trajectory are analyzed to identify the intrinsic characteristics of the application traffic. Analyses show that the nonlinear dynamic features can accurately characterize application traffic behavior and that these features are independent of the network scale and Internet protocol version. Therefore, the nonlinear dynamics of application traffic can be used to improve network traffic classification.
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