Accurate approximation of cell loss probability for self-similartraffic in ATM networks

Recently, self-similar (or fractal) stochastic processes have been regarded as more accurate models of certain categories of traffic (e.g. LAN traffic) which will be transported in ATM networks. The authors propose a method for estimating the cell loss probability in an ATM multiplexer fed by a self-similar arrival process. The packet arrivals are generated by a fractional Brownian motion process and the service process is deterministic. The approach is based on theory for large deviations, and simulation tests show that it is more accurate than the existing approximation result