Perfect sampling for multiclass closed queueing networks

Anne Bouillard 1, 2, 3 Ana Busic 2, 3 Christelle Rovetta 1, 2, 3
2 DYOGENE - Dynamics of Geometric Networks
DI-ENS - Département d'informatique de l'École normale supérieure, Inria Paris-Rocquencourt, CNRS - Centre National de la Recherche Scientifique : UMR8548
Abstract : In this paper we present an exact sampling method for multiclass closed queuing networks. We consider networks for which stationary distribution does not necessarily have a product form. The proposed method uses a compact representation of sets of states, that is used to derive a bounding chain with significantly lower complexity of one-step transition in the coupling from the past scheme. The coupling time of this bounding chain can be larger than the coupling time of the exact chain, but it is finite in expectation. Numerical experiments show that coupling time is close to that of the exact chain. Moreover, the running time of the proposed algorithm outperforms the classical algorithm.
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Anne Bouillard, Ana Busic, Christelle Rovetta. Perfect sampling for multiclass closed queueing networks. 12th International Conference on Quantitative Evaluation of SysTems (QEST 2015) , Sep 2015, Madrid, Spain. ⟨hal-01159962⟩

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