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.
Embedded Processes in Generalized Stochastic Petri Nets
BALBO, Gianfranco;SERENO, Matteo
2001-01-01
Abstract
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.
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