Lumping partially symmetrical stochastic models

Souheib Baarir 1 Marco Beccuti 2 Claude Dutheillet 1 Giuliana Franceschinis 3 Serge Haddad 4
1 MoVe - Modélisation et Vérification
LIP6 - Laboratoire d'Informatique de Paris 6
4 MEXICO - Modeling and Exploitation of Interaction and Concurrency
LSV - Laboratoire Spécification et Vérification [Cachan], ENS Cachan - École normale supérieure - Cachan, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8643
Abstract : The performance and dependability evaluation of complex systems by means of dynamic stochastic models (e.g. Markov chains) may be impaired by the combinatorial explosion of their state space. Among the possible methods to cope with this problem, symmetry-based ones can be applied to systems including several similar components. Often however these systems are only partially symmetric: their behavior is in general symmetric except for some local situation when the similar components need to be differentiated. In this paper two methods to efficiently analyze partially symmetrical models are presented in a general setting and the requirements for their efficient implementation are discussed. Some case studies are presented to show the methods' effectiveness and their applicative interest.
Type de document :
Article dans une revue
Performance Evaluation, Elsevier, 2011, 68 (1), pp.21-44. 〈10.1016/j.peva.2010.09.002〉
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Soumis le : mardi 22 janvier 2013 - 17:27:45
Dernière modification le : dimanche 9 décembre 2018 - 01:23:27



Souheib Baarir, Marco Beccuti, Claude Dutheillet, Giuliana Franceschinis, Serge Haddad. Lumping partially symmetrical stochastic models. Performance Evaluation, Elsevier, 2011, 68 (1), pp.21-44. 〈10.1016/j.peva.2010.09.002〉. 〈hal-00779940〉



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