Stochastic Petri Nets (SPNs) have recently emerged as a principal performance modelling tool for distributed systems such as multiprocessors, local area networks, and automated manufacturing systems. Since the use of SPNs as an analytical tool is based on the generation of the entire state space, the technique becomes intractable for large systems. In such cases, discrete event simulation is the preferred tool for performance evaluation. In this paper, we show how SPNs can be used as a simulation model. We present several efficient algorithms based on SPNs, for conducting discrete event simulations of distributed systems.
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