Modeling and simulation of self-similar traffic based on FBM model

Network traffic models are important basis of network programming and performance evaluation.The conventional models are mostly based on Poisson model and Markovian traffic model,which is only Short-Range Dependence.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,the RMD and Fourier algorithm were adopted to simulate and analyze FBM model,a self-similar model.They generated the necessary sequence of self-similar traffic.Then the article uses R/S method and variance-time method to verify Hurst 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.