Process algebras for quantitative analysis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

In the 1980s process algebras became widely accepted formalisms for describing and analysing concurrency. Extensions of the formalisms, incorporating some aspects of systems which had previously been abstracted, were developed for a number of different purposes. In the area of performance analysis models must quantify both timing and probability. Addressing this domain led to the formulation of stochastic process algebras. In this paper we give a brief overview of stochastic process algebras and the problems which motivated them, before focussing on their relationship with the underlying mathematical stochastic process. This is presented in the context of the PEPA formalism.
Original languageUndefined/Unknown
Title of host publicationLogic in Computer Science, 2005. LICS 2005. Proceedings. 20th Annual IEEE Symposium on
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages10
ISBN (Print)0-7695-2266-1
Publication statusPublished - 1 Jun 2005

Keywords / Materials (for Non-textual outputs)

  • probability
  • process algebra
  • stochastic processes
  • PEPA formalism
  • mathematical stochastic process
  • performance analysis model
  • process algebras
  • quantitative analysis
  • Algebra
  • Concurrent computing
  • Context
  • Informatics
  • Markov processes
  • Performance analysis
  • Power system modeling
  • Sparse matrices
  • Stochastic processes
  • Timing

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