PEPERCORN: inferring performance models from location tracking data

Authors:
Nikolas Anastasiou;William Knottenbelt
Affiliations:
Department of Computing, Imperial College London, London, UK;Department of Computing, Imperial College London, London, UK
Venue:
QEST'13 Proceedings of the 10th international conference on Quantitative Evaluation of Systems
Year:
2013

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Abstract

Stochastic performance models are widely used to analyse the performance of systems that process customers and resources. However, the construction of such models is traditionally manual and therefore expensive, intrusive and prone to human error. In this paper we introduce PEPERCORN, a Petri Net Performance Model (PNPM) construction tool, which, given a dataset of raw location tracking traces obtained from a customer-processing system, automatically formulates and parameterises a corresponding Coloured Generalised Stochastic Petri Net (CGSPN) performance model.