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Markovian process algebras, such as PEPA and stochastic π-calculus, bring a powerful compositional approach to the performance modelling of complex systems. However, the models generated by process algebras , as with other interleaving formalisms, are susceptible to the state space explosion problem. Models with only a modest number of process algebra terms(More)
—We extend the mean-field (a.k.a. fluid-analysis) approach for massively-parallel continuous-time Markov chains (CTMCs) to models with both Markovian and deterministically-timed transitions. We introduce a new low-level formalism for specifying massively-parallel models with generally-timed transitions , the population generalised semi-Markov process(More)
Rapid and accessible performance evaluation of complex software systems requires two critical features: the ability to specify useful performance metrics easily and the capability to analyze massively distributed architectures, without recourse to large compute clusters. We present the unified stochastic probe, a performance specification mechanism for(More)
—We present a tool called Grouped PEPA Analyser (GPA) that allows fast analysis of large scale models described in the stochastic process algebra PEPA. GPA employs the techniques for approximations of transient moments in PEPA models with ordinary differential equations (ODEs), which allow analysis of systems with state spaces far beyond the limits of(More)
Fluid modelling is a next-generation technique for analysing massive performance models. Passive cooperation is a popular cooperation mechanism frequently used by performance engineers. Therefore having an accurate translation of passive cooperation into a fluid model is of direct practical application. We compare different existing styles of fluid model(More)
We extend the population continuous time Markov chain formalism so that the state space is augmented with continuous variables accumulated over time as functions of component populations. System feedback can be expressed using accumulations that in turn can influence the Markov chain behaviour via functional transition rates. We show how to obtain(More)
Achieving the appropriate performance requirements for computer– communication systems is as important as the correctness of the end-result. This is particularly difficult in the case of massively parallel computer systems such as the clusters of PCs behind the likes of Google and peer-to-peer filesharing networks such as Bittorrent. Measuring the(More)
—We present a significant extension to the Grouped PEPA Analyser (GPA) tool. We have augmented the tool with the ability to specify complex passage-time distributions with the Unified Stochastic Probes formalism and implemented efficient fluid analysis techniques to compute the distributions. The extension incorporates immediate signalling and weighted(More)