Solving product form stochastic networks with Monte Carlo summation

Keith W. Ross, Jie Wang

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


    Multiclass queuing networks and stochastic loss networks often give rise to a product form solution for their equilibrium probabilities, but the product form solution typically involves a normalization constant calling for a multidimensional summation over an astronomical number of states. The authors propose the application of Monte Carlo summation to the problem of determining the normalization constant and related performance measures. It is shown that if the proper sampling technique is used then the computational effort of Monte Carlo summation is independent of link capacities for loss networks. The application of importance sampling and antithetic variates is then discussed. Importance sampling is shown to give significant variance reduction for a multirate loss network example.

    Original languageEnglish (US)
    Title of host publication90 Winter Simulation Conf.
    PublisherPubl by IEEE
    Number of pages6
    ISBN (Print)0911801723
    StatePublished - Dec 1990
    Event1990 Winter Simulation Conference Proceedings - New Orleans, LA, USA
    Duration: Dec 9 1990Dec 12 1990

    Publication series

    NameWinter Simulation Conference Proceedings
    ISSN (Print)0275-0708


    Other1990 Winter Simulation Conference Proceedings
    CityNew Orleans, LA, USA

    ASJC Scopus subject areas

    • Software
    • Modeling and Simulation
    • Safety, Risk, Reliability and Quality
    • Chemical Health and Safety
    • Applied Mathematics


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