Stochastic high-level Petri nets and applications

Abstract

A class of stochastic Petri nets called stochastic high-level Petri nets (SHLPNs) is proposed. SHLPNs are high-level Petri nets augmented with exponentially distributed firing times. SHLPNs generally lead to models with a smaller state space. A computer marking concept is introduced that allows a considerable reduction of the number of states and induces a correct grouping of states in the Markov-domain SHLPN models of multiprocessor systems. The main advantage of modeling homogeneous systems using SHLPNs is that the resulting models are simpler and more intuitive and have a smaller number of states, as shown by examples.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>