Research On The Self-Similarities Of Network Traffic And Relative Generation Methods

Self-Similar Property is one of the key statistical characteristics in the computer networks(including LAN and WAN).Self-Similar traffic has a significant impact on network management and control as well as performance evaluation. This paper carries on an extensive investigation and deep research on modeling Self-Similar traffic in many aspects like statistical analysis of traffic, description of Self-Similar process, generation of sequences, multi-fractal analysis and so on. The main contributions in this paper are as follows:l)Summarize the overall issues in the area of Self-Similar modeling and control.2)Analyze the statistical characteristics of the traffic in the computer network and prove the fact that Self-Similarity is a common property. Discuss the issue on estimating the Hurst parameter of Self-Similar traffic.3)Discuss the validity(Self-Similarity first of all) of the NS2 simulating traffic(like UDP and TCP).4)Summarize some of the Self-Similar process and Self-Similar traffic generation methods.5) Propose a new method to generate Self-Similar traffic based on RMD method. analyze its accurately and promptly.6)Apply the method of multi-fractal analysis to analyze the fractal behavior of Self-Similar traffic in computer networks and simulating trace in NS2.