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Embedded processes in Generalized Stochastic Petri Nets

We show that a particular class of Generalized Stochastic Petri Nets have stationary probabilities that exhibit a product form. Efficient solution algorithms can be developed for the computation of the performance indices of such Product-Form GSPNs. These algorithms avoid the generation of the underlying state space. Hence, large PF-GSPN models can now be effectively studied.