Modeling of traffic sources in ATM networks

ATM networks integrate different communication services such as data, voice and video, which have different traffic characteristics. To evaluate the performance of ATM networks, accurate traffic models that can capture the statistical characteristics of actual traffic are required. The traffic models are employed either as part of an analytical model, or to drive a discrete event simulation. This paper reviews the modeling techniques of traffic sources in ATM networks. The traffic models can be classified into short-range and long-range dependent models. Short-range dependent models such as renewal models, Markov and Markov modulated processes, and regression models were introduced in this paper.