In: Proceedings of 9th International Workshop on Petri Nets and Performance Models, PNPM'01 Aachen, Sept. 11-14, 2001, Reinhard German and Boudewijn Haverkort (eds.), IEEE, pages 81-90. 2001.
Abstract: Markov chain based analysis of GSPNs suffers from the state space explosion problem. In this paper we combine ideas from two different other approaches to analysze sytems with very large state spaces. First, we represent the generator matrix as a sum of Kronecker products of small component matrices. Second, we use an extension of probabilistic decision graphs to represent probability vectors. The combination of these two concepts is the base for an iterative solution technique with the potential to handle extremely large Markov chains resulting from Superposed GSPNs or related model types.
Keywords: Superposed GSPN, Numerical Analysis, Kronecker Representation, Probabilistic Decision Graph.
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