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PEPERCORN: Inferring Performance Models from Location Tracking Data

  • Nikolas Anastasiou
  • William Knottenbelt
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8054)

Abstract

Stochastic performance models are widely used to analyse the performance of systems that process customers and resources. However, the construction of such models is traditionally manual and therefore expensive, intrusive and prone to human error. In this paper we introduce PEPERCORN, a Petri Net Performance Model (PNPM) construction tool, which, given a dataset of raw location tracking traces obtained from a customer-processing system, automatically formulates and parameterises a corresponding Coloured Generalised Stochastic Petri Net (CGSPN) performance model.

Keywords

Performance Modelling Location Tracking Data Mining Coloured Generalised Stochastic Petri Nets 

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Nikolas Anastasiou
    • 1
  • William Knottenbelt
    • 1
  1. 1.Department of ComputingImperial College LondonLondonUK

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