ATM admission models of stochastic high level Petri nets based on hierarchical modeling

This paper presents a framework for modeling and analyzing ATM admission control using Stochastic High Level Petri Net (SHLPN). SHLPN is chosen because it is a powerful graphical and mathematical modeling tool that is able to handle concurrent, asynchronous, nondeterministic and stochastic events. In addition, there exists a set of well-developed performance analysis techniques for SHLPN. This paper uses a hierarchical modeling technique to specify complex ATM network mechanisms using a top-down approach. However, in analyzing the performance of the network, a bottom-up approach is adopted. To tackle the state space explosion problem, a SHLPN model is decomposed into submodels. These subnets are independently evaluated with all possible population which are then substituted by transitions with approximate equivalent performance in the original model. The technique is illustrated by modeling and evaluating a specific connection admission control policy