In: PNPM89. Proceedings of the Third International Workshop On Petri Nets and Performance Models, 1989, Kyoto, Japan, pages 221-227. Los Alamitos, CA, USA: IEEE Computer Society Press, 1990.
Abstract: The authors present methods to compute tight bounds for steady-state token probabilities of a class of Generalized Stochastic Petri Net (GSPN) models. The authors describe a method to compute the best lower and upper bounds for conditional token probabilities of a class of GSPN subnets and show that such bounds can be improved if additional information about other subnets is available. They then extend the technique and outline an algorithm to compute the bounds for error due to aggregation and decomposition at the GSPN level.
Keywords: generalized stochastic net; steady-state token probability.
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