A new approach for ATM network traffic modeling and simulation

The main objective of this paper is to develop a tractable model for self-similar traffic and to apply it to ATM networks. We develop a new traffic model derived from the arrival processes of the type M/G/∞. This modeling method not only provides us an explicit and analytical expression for the self-similar traffic processes, but also sets up a connection between the two most popular self-similar processes. This model has a structure similar to that of a fractional ARIMA, with a driven process of fBm (fractional Brownian motion). But the coefficients of the fBm are derived from the Pareto distribution of the active periods of the arrival process. We also derive an explicit buffer level equation based on the proposed traffic model, which matches Norros´ (1994) storage model. So this method can be also served as a verification of Norros´ assumptions. The queueing behavior of a single server to self-similar input can be analytically investigated with the proposed equation. The effectiveness of these methods has been demonstrated by some practical applications