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

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. Copyright © 2011 ICST.