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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. The paper analyses the time-dependent behaviour of an automotive rescue service in the context of uncertainty about durations. It deploys 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 the high-level formal model of the service expressed in a stochastic process algebra.

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Format:PDFSize:291 KB
Date:Jun 2006
Pages:14

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