A class of generalized stochastic Petri nets for the performance evaluation of multiprocessor systems

di Torino, Turin, Italy Generalized Stochastic Petri Nets (GSPNs) are presented and are applied to the performance evaluation of multiprocessor systems. GSPNs are derived from standard Petri nets by partitioning the set of transitions into two subsets comprising timed and immediate ransitions. An exponentially distributed random firing time is associated with each timed transition, whereas immediate ransitions fire in zero time. It is shown that GSPNs are equivalent to continuous-time stochastic processes, and solution methods for the derivation of the steady state probability distribution are presented. Examples of application of GSPN models to the performance evaluation of multiprocessor systems show the usefulness and the effectiveness of this modeling tool. 1