Probabilistic KLAIM

  • Alessandra Di Pierro
  • Chris Hankin
  • Herbert Wiklicky
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2949)


We introduce a probabilistic extension of KLAIM, where the behaviour of networks and individual nodes is determined by a probabilistic scheduler for processes and probabilistic allocation environments which describe the logical neighbourhood of each node. The resulting language has two variants which are modelled respectively as discrete and continuous time Markov processes. We suggest that Poisson processes are a natural probabilistic model for the coordination of discrete processes asynchronously communicating in continuous time and we use them to define the operational semantics of the continuous time variant. This framework allows for the implementation of networks with independent clocks on each site.


Continuous Time Operational Semantic Global Transition Continuous Time Model Discrete Time Markov Chain 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Alessandra Di Pierro
    • 1
  • Chris Hankin
    • 2
  • Herbert Wiklicky
    • 2
  1. 1.Dipartimento di InformaticaUniversità di PisaItaly
  2. 2.Department of ComputingImperial College LondonUK

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