Deriving generalised stochastic Petri net performance models from high-precision location tracking data

نویسندگان

  • Nikolas Anastasiou
  • Tzu-Ching Horng
  • William J. Knottenbelt
چکیده

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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تاریخ انتشار 2011