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Deriving Generalised Stochastic Petri Net performance models from high-precision location tracking data

Nikolas Anastasiou, Tzu-Ching Horng, William J. Knottenbelt

Conference or Workshop Paper
Fifth International Conference on Performance Evaluation Methodologies and Tools (VALUETOOLS 2011)
April, 2011
Abstract

Stochastic performance models have been widely used to analyse the performance and reliability of systems that involve the flow and processing of customers and/or resources with multiple service centres. However, the quality of performance analysis delivered by a model depends critically on the degree to which the model accurately represents the operations of the real system. This paper presents an automated technique which takes as input high-precision location tracking data - potentially collected from a real life system and constructs a hierarchical Generalised Stochastic Petri Net performance model of the underlying system. We examine our method's effectiveness and accuracy through two case studies based on synthetic location tracking data.

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Information from pubs.doc.ic.ac.uk/petri-net-from-location-data.