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Performance analysis of Stochastic Process Algebra models using Stochastic Simulation

Jeremy T. Bradley, Stephen T. Gilmore, Nigel Thomas

Conference or Workshop Paper
PMEO-PDS'06, Proceedings of Performance Modelling, Evaluation and Optimization of Parallel and Distributed Systems
March, 2006
IEEE Computer Society Press

We present a translation of a generic stochastic process algebra model into a form suitable for stochastic simulation. By systematically generating rate equations from a process description, we can use tools developed for chemical and biochemical reaction analysis to provide time-series output for models with state spaces of O(10^10000) and beyond. We apply these techniques to asignificant case study: that of a secure electronic voting protocol.

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