Stochastic Petri nets for modelling and simulation

Stochastic Petri nets (SPNs) have proven to be a powerful and enduring graphically-oriented framework for modelling and performance analysis of complex systems. This tutorial focuses on the use of SPNs in discrete-event simulation. After describing the basic SPN building blocks and discussing the modelling power of the formalism, we present elements of a steady-state simulation theory for SPNs. Specifically, we provide conditions on the building blocks of an SPN that ensure long-run stability for the underlying marking process (or for a sequence of delays determined by the marking process) and the validity of estimation procedures such as the regenerative method, the method of batch means, and spectral methods.