Modeling ATM traffic using stochastic Petri net

Abstract

This paper describes a general framework for modeling and analyzing ATM traffic control using the stochastic high level Petri net (SHLPN). The reasons SHLPN is chosen are two fold: it can handle concurrent, asynchronous, nondeterministic and stochastic events; and it provides an intuitive yet efficient mechanism that can decompose a complex model into submodels. In addition, there exists a set of well-developed performance analysis techniques for SHLPN. In order to cope with the well known state space explosion problem, we proposed a novel reduction method which incorporates the bursty characteristic of ATM networks. We show how to apply the SHLPN techniques in modeling and analyzing various ATM mechanisms such as: bursty traffic source and traffic rate control.