Modeling and Simulation of Self-Similar Traffic for Wireless IP Networks

The paper examines self-similar properties of real telecommunications network traffic data over a wide range of time scales. These self-similar properties are very different from the properties of traditional models based on Poisson and Markov-modulated Poisson processes. The algorithms for modeling fixed-length sequence generators that are used to simulate self-similar behavior of wireless IP network traffic are developed and applied. The implementation of suggested simulation approach for stochastic and long range dependence teletraffic source models is shown. Buffer overflow simulation for finite buffer single server model under self-similar traffic load SSM/M/1/B is considered. Numerical examples and simulation results are provided.