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Iterative analysis of Markov regenerative models.

German, R.

In: Lecture Notes in Computer Science, Vol. 1786: Computer Performance Evaluation: Modeling Techniques and Tools, pages 156-170. Springer-Verlag, 2000.

Abstract: Conventional algorithms for the steady-state analysis of Markov regenerative models suffer from high computational costs which are caused by densely populated matrices. In this paper a new algorithm is suggested which avoids to compute these matrices explicitly. Instead, a two-stage iteration scheme is used. An extended version of uniformization is applied as a subalgorithm to compute the required transient quantities ``on the fly''. The algorithm is formulated in term of stochastic Petri nets. A detailed example illustrates the proposed concepts.

Keywords: Markov regenerative models, iterative analysis, stochastic Petri nets.

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