Distributed Response Time Analysis of GSPN Models with MapReduce

widely used in the performance analysis of computer and communications systems. Response time densities and quantiles are often key outputs of such analysis. These can be extracted from a GSPN’s underlying semi-Markov process using a method based on numerical Laplace transform inversion. This method typically requires the solution of thousands of systems of complex linear equations, each of rank n, where n is the number of states in the model. For large models substantial processing power is needed and the computation must therefore be distributed. This paper describes the implementation of a Response Time Analysis module for the Platform Independent Petri net Editor (PIPE2) which interfaces with Hadoop, an open source implementation of Google’s MapReduce distributed programming environment, to provide distributed calculation of response time densities in GSPN models. The software is validated with analytically calculated results as well as simulated ones for larger models. Excellent scalability is shown. I

Evaluating Quality of Service for Service Level Agreements

Quantitative analysis of quality-of-service metrics is an important tool in early evaluation of service provision. This analysis depends on being able to estimate the average duration of critical activities used by the service but at the earliest stages of service planning it may be impossible to obtain accurate estimates of the expected duration of these activities. We analyse the time-dependent behaviour of an automotive rescue service in the context of uncertainty about durations. We deploy a distributed computing platform to allow the efficient derivation of quantitative analysis results across the range of possible values for assignments of durations to the symbolic rates of our high-level formal model of the service expressed in a stochastic process algebra

Modelling Role-Playing Games Using PEPA Nets

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