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.
Information from pubs.doc.ic.ac.uk/sync-detection-petrinet.