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Hierarchical solution of generalized Stochastic Petri Nets by means of traffic processes

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Application and Theory of Petri Nets 1992 (ICATPN 1992)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 616))

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Abstract

A methodology is presented for the approximate solution of large Stochastic Petri Nets that are structured into independent submodels. These subnets are aggregated to substitute nets of lower complexity to achieve a state space reduction. This is based on the estimated traffic process at a submodel's input in steady state and on a token's residence time distribution in the original submodel as equivalence criterion for matching the substitute network to the submodel. The Markov renewal process at the input of the submodel is approximated by a renewal process. Its moments and the arrival instant probabilities at the submodel are computed by means of a traffic set approach. The technique is applied to Generalized Stochastic Petri Nets and compared to Flow Equivalent Aggregation.

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Authors and Affiliations

  1. Siemens Corporate R&D, Otto-Hahn Ring, 6,8000, Munich 83, Germany

    Guenter Klas

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  1. Guenter Klas
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K. Jensen

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© 1992 Springer-Verlag Berlin Heidelberg

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Klas, G. (1992). Hierarchical solution of generalized Stochastic Petri Nets by means of traffic processes. In: Jensen, K. (eds) Application and Theory of Petri Nets 1992. ICATPN 1992. Lecture Notes in Computer Science, vol 616. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-55676-1_16

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  • DOI: https://doi.org/10.1007/3-540-55676-1_16

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-55676-3

  • Online ISBN: 978-3-540-47270-4

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