Reactive, generative, and stratified models of probabilistic processes
Information and Computation
Performance measure sensitive congruences for Markovian process algebras
Theoretical Computer Science
Formal Specification of Performance Measures for Process Algebra Models of Concurrent Systems
Formal Specification of Performance Measures for Process Algebra Models of Concurrent Systems
Compositional Asymmetric Cooperations for Process Algebras with Probabilities, Priorities, and Time
Compositional Asymmetric Cooperations for Process Algebras with Probabilities, Priorities, and Time
Theory and Application of Extended Markovian Process Algebra (PhD Thesis)
Theory and Application of Extended Markovian Process Algebra (PhD Thesis)
Stochastic Process Algebra: From an Algebraic Formalism to an Architectural Description Language
Performance Evaluation of Complex Systems: Techniques and Tools, Performance 2002, Tutorial Lectures
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In this paper we extend a performance measure sensitive Markovian bisimulation congruence based on yield and bonus rewards that has been previously defined in the literature, in order to aggregate more states and transitions while preserving compositionality and the values of the performance measures. The extension is twofold. First, we show how to define a performance measure sensitive Markovian bisimulation congruence that aggregates bonus rewards besides yield rewards. This is achieved by taking into account in the aggregation process the conditional execution probabilities of the transitions to which the bonus rewards are attached. Second, we show how to define a performance measure sensitive Markovian bisimulation congruence that allows yield rewards and bonus rewards to be used interchangeably up to suitable correcting factors, aiming at the introduction of a normal form for rewards. We demonstrate that this is possible in the continuous time case, while it is not possible in the discrete time case because compositionality is lost.