Automating the mean-field method for large dynamic gossip networks

Rena Bakhshi, Jörg Endrullis, Stefan Endrullis, Wan Fokkink, Boudewijn R.H.M. Haverkort

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    15 Citations (Scopus)
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    We investigate an abstraction method, called mean- field method, for the performance evaluation of dynamic net- works with pairwise communication between nodes. It allows us to evaluate systems with very large numbers of nodes, that is, systems of a size where traditional performance evaluation methods fall short. While the mean-field analysis is well-established in epidemics and for chemical reaction systems, it is rarely used for commu- nication networks because a mean-field model tends to abstract away the underlying topology. To represent topological information, however, we extend the mean-field analysis with the concept of classes of states. At the abstraction level of classes we define the network topology by means of connectivity between nodes. This enables us to encode physical node positions and model dynamic networks by allowing nodes to change their class membership whenever they make a local state transition. Based on these extensions, we derive and implement algorithms for automating a mean-field based performance evaluation.
    Original languageUndefined
    Title of host publicationProceedings of the 7th International Conference on the Quantitative Evaluation of Systems (QEST 2010)
    Place of PublicationUSA
    Number of pages10
    ISBN (Print)978-0-7695-4188-4
    Publication statusPublished - Sept 2010
    Event7th International Conference on Quantitative Evaluation of SysTems, QEST 2010 - College of William & Mary, Williamsburg, United States
    Duration: 15 Sept 201018 Sept 2010
    Conference number: 7

    Publication series

    PublisherIEEE Computer Society


    Conference7th International Conference on Quantitative Evaluation of SysTems, QEST 2010
    Abbreviated titleQEST
    Country/TerritoryUnited States
    Internet address


    • METIS-276245
    • EWI-19152
    • IR-75339

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