A New Self-Similar Traffic Model and its Applications in Telecommunication Networks

This paper presents a new self-similar traffic model derived from the arrival processes of M/G/∞ queue. It has a structure similar to that of a fractional ARIMA, with a driven process of fBm (fractional Brownian motion). The coefficients of the fBm are derived from the Pareto distribution of the active periods of the arrival process. When applied to a single server with self-similar input, the model results in an explicit buffer level equation which matches Norros’ storage model. So this method can be also served as a verification of Norros’ assumptions. The effectiveness of the proposed model has been verified by some practical examples.