Simulation of Self-similarFlowBased on Fractal Gaussian Noise Method

The conventional network traffic flow models are mostly based on Poisson model. With the continuous development of network services, studies found that the actual network traffic has a long-range dependence (LRD) now and in a very long time, which is a kind of self-similarity. In this paper, RMD and Fourier algorithm were adopted to simulate and analyze a self-similar model of FGN. They generated the necessary sequence of self-similar traffic. Then the article uses R/S method to verify H value of the generated sequence of self-similar traffic in order to verify the self-similarity of the self-similar traffic sequence. The existence of self-similarity is verified by experiments, and the advantage and disadvantage of RMD and Fourier algorithm are analyzed.