On the solution of GSPN reward models
Performance Evaluation
Stochastic Automata Network of Modeling Parallel Systems
IEEE Transactions on Software Engineering
A compositional approach to performance modelling
A compositional approach to performance modelling
Composition and behaviors of probabilistic I/O automata
Theoretical Computer Science
Lumping Markov Chains with Silent Steps
QEST '06 Proceedings of the 3rd international conference on the Quantitative Evaluation of Systems
Compositionality for Markov reward chains with fast and silent transitions
Performance Evaluation
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A parallel composition is defined for Markov reward chains with fast transitions and for discontinuous Markov reward chains. In this setting, compositionality with respect to the relevant aggregation preorders is established. For Markov reward chains with fast transitions the preorders are τ -lumping and τ -reduction. Discontinuous Markov reward chains are 'limits' of Markov reward chains with fast transitions, and have related notions of lumping and reduction. In total, four compositionality results are shown. In addition, the two parallel operators are related by a continuity property.