Time scale analysis of an ATM queueing system with long-range dependent traffic

Several types of network traffic have been shown to exhibit long-range dependence (LRD). In this work, we show that the busy period of an ATM system driven by a long-range dependent process can be very large. We introduce a new traffic model based on a fractional Brownian motion envelope process. We show that this characterization can be used to predict queueing dynamics. Furthermore, we derive a new framework for computing delay bounds in ATM networks based on this traffic model. We show that it agrees with results given by large deviation theory with less computational complexity