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Investigating Parametric Influence on Discrete Synchronisation Protocols Using Quantitative Model Checking

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Quantitative Evaluation of Systems (QEST 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10503))

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Abstract

Synchronisation is an emergent phenomenon observable in nature. Natural synchronising systems have inspired the development of protocols for achieving coordination in a diverse range of distributed dynamic systems. Spontaneously synchronising systems can be mathematically modelled as coupled oscillators. In this paper we present a novel approach using model checking to reason about achieving synchrony for different models of synchronisation. We describe a general, formal population model where oscillators interact at discrete moments in time, and whose cycles are sequences of discrete states. Using the probabilistic model checker Prism, we investigate the influence of various parameters of the model on the likelihood of, and time required for, achieving synchronisation.

This work was supported by both the Sir Joseph Rotblat Alumni Scholarship at Liverpool and the EPSRC Research Programme EP/N007565/1 Science of Sensor System Software.

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Notes

  1. 1.

    The model generation script and the results presented in this paper can be found at https://github.com/PaulGainer/mc-bio-synch.

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Authors and Affiliations

  1. University of Liverpool, Liverpool, UK

    Paul Gainer, Sven Linker, Clare Dixon, Ullrich Hustadt & Michael Fisher

Authors
  1. Paul Gainer
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  2. Sven Linker
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  3. Clare Dixon
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  4. Ullrich Hustadt
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  5. Michael Fisher
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Corresponding author

Correspondence to Paul Gainer .

Editor information

Editors and Affiliations

  1. Inria, Rennes, France

    Nathalie Bertrand

  2. University of Trieste, Trieste, Italy

    Luca Bortolussi

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Gainer, P., Linker, S., Dixon, C., Hustadt, U., Fisher, M. (2017). Investigating Parametric Influence on Discrete Synchronisation Protocols Using Quantitative Model Checking. In: Bertrand, N., Bortolussi, L. (eds) Quantitative Evaluation of Systems. QEST 2017. Lecture Notes in Computer Science(), vol 10503. Springer, Cham. https://doi.org/10.1007/978-3-319-66335-7_14

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  • DOI: https://doi.org/10.1007/978-3-319-66335-7_14

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  • Print ISBN: 978-3-319-66334-0

  • Online ISBN: 978-3-319-66335-7

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