The inference of performance models from low-level location tracking traces provides a means to gain high-level insight into customer and/or resource flow in complex systems. In this context our earlier work presented a methodology for automatically constructing Petri Net performance models from location tracking data. However, the capturing of synchronisation between service centres - the natural expression of which is one of the most fundamental advantages of Petri nets as a modelling formalism - was not explicitly supported. In this paper, we introduce mechanisms for automatically detecting and incorporating synchronisation into our existing methodology. We present a case study based on synthetic location tracking data where the derived synchronisation detection mechanism is applied. © 2011 Springer-Verlag.
CITATION STYLE
Anastasiou, N., Knottenbelt, W., & Marin, A. (2011). Automatic synchronisation detection in Petri Net performance models derived from location tracking data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6977 LNCS, pp. 29–41). https://doi.org/10.1007/978-3-642-24749-1_4
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