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  COMBINING AGGREGATION AND DECOMPOSITION METHODS FOR PERFORMANCE EVALUATION OF COMPLEX SYSTEMS

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by Patrice Moreaux
http://www.lamsade.dauphine.fr/~moreaux/compswn/iscixi.ps.gz
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Abstract:

To reduce the complexity of computation of performance indices of parallel systems, we present a new exact method combining the aggregation and decomposition methods of the state space. Aggregation is performed by the use of the Stochastic Well-Formed Net (SWN) Petri Net model and decomposition follows tensor methods initiated by Plateau. We generalize our previous work to provide results for asynchronous as well as synchronous composition of submodels. We highlight the problems of such an approach and we derive necessary conditions on the modelled systems that allow for the two methods to be combined. For parallel systems satisfying these necessary conditions, we develop models with corresponding algorithms.

Citations

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2 Aggregation and decomposition for performance evaluation of synchronous product of high level Petri nets – Haddad, Moreaux - 1996
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