ACCURATE APPROXIMATION OF CELL LOSS PROBABILITY FOR SELF-SIMILAR TRAFFIC IN ATM NETWORKS

Recently, self-similar (or fractal) stochastic processes have been reg arded as more accurate models of certain categories of traffic (e.g. L AN traffic) which will be transported in ATM networks. The authors pro pose a method for estimating the cell loss probability in an ATM multi plexer fed by a self-similar arrival process. The packet arrivals are generated by a fractional Brownian motion process and the service proc ess is deterministic. The approach is based on theory for large deviat ions, and simulation tests show that it is more accurate than the exis ting approximation result.