Approximate mean value analysis for stochastic marked graphs
Matteo Sereno · IEEE Transactions on Software Engineering · 1996
An iterative technique for the computation of approximate performance indices of a class of stochastic Petri net models is presented. The proposed technique is derived from the mean value analysis algorithm for product-form solution stochastic Petri nets. In this paper, we apply the approximation technique to stochastic marked graphs. In principle, the proposed technique can be used for other stochastic Petri net subclasses. In this paper, some of these possible applications are presented. Several examples are presented in order to validate the approximate results.