Efficient Simulation of Population Overflow in Parallel Queues

V.F. Nicola, T.S. Zaburnenko

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    1 Citation (Scopus)
    64 Downloads (Pure)

    Abstract

    In this paper we propose a state-dependent importance sampling heuristic to estimate the probability of population overflow in networks of parallel queues. This heuristic approximates the “optimal��? state-dependent change of measure without the need for dif��?cult mathematical analysis or costly optimization involved in adaptive methodologies. Comprehensive simulations of networks with an arbitrary number of parallel queues and different traf��?c intensities yield asymptotically ef��?cient estimates (with relative error increasing sub-linearly in the overflow level) where no other state-independent importance sampling techniques are known to be ef��?cient. The ef��?ciency of the proposed heuristic surpasses those based on adaptive importance sampling algorithms, yet it is easier to determine and implement and scales better for large networks.
    Original languageUndefined
    Title of host publicationProceedings of the 2006 Winter Simulation Conference, WSC'06
    PublisherWSC
    Pages398-405
    Number of pages8
    ISBN (Print)1424405017
    Publication statusPublished - Dec 2006
    Event2006 Winter Simulation Conference - Monterey, United States
    Duration: 3 Dec 20066 Dec 2006

    Publication series

    Name
    PublisherWSC
    Number06EX1382C

    Conference

    Conference2006 Winter Simulation Conference
    Abbreviated titleWSC 2006
    CountryUnited States
    CityMonterey
    Period3/12/066/12/06
    Other3 - 6 December 2006

    Keywords

    • EWI-9066
    • METIS-237909
    • IR-66871

    Cite this

    Nicola, V. F., & Zaburnenko, T. S. (2006). Efficient Simulation of Population Overflow in Parallel Queues. In Proceedings of the 2006 Winter Simulation Conference, WSC'06 (pp. 398-405). WSC.
    Nicola, V.F. ; Zaburnenko, T.S. / Efficient Simulation of Population Overflow in Parallel Queues. Proceedings of the 2006 Winter Simulation Conference, WSC'06. WSC, 2006. pp. 398-405
    @inproceedings{e209497072564a5ca31eb1cd88e14170,
    title = "Efficient Simulation of Population Overflow in Parallel Queues",
    abstract = "In this paper we propose a state-dependent importance sampling heuristic to estimate the probability of population overflow in networks of parallel queues. This heuristic approximates the “optimal��? state-dependent change of measure without the need for dif��?cult mathematical analysis or costly optimization involved in adaptive methodologies. Comprehensive simulations of networks with an arbitrary number of parallel queues and different traf��?c intensities yield asymptotically ef��?cient estimates (with relative error increasing sub-linearly in the overflow level) where no other state-independent importance sampling techniques are known to be ef��?cient. The ef��?ciency of the proposed heuristic surpasses those based on adaptive importance sampling algorithms, yet it is easier to determine and implement and scales better for large networks.",
    keywords = "EWI-9066, METIS-237909, IR-66871",
    author = "V.F. Nicola and T.S. Zaburnenko",
    year = "2006",
    month = "12",
    language = "Undefined",
    isbn = "1424405017",
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    number = "06EX1382C",
    pages = "398--405",
    booktitle = "Proceedings of the 2006 Winter Simulation Conference, WSC'06",

    }

    Nicola, VF & Zaburnenko, TS 2006, Efficient Simulation of Population Overflow in Parallel Queues. in Proceedings of the 2006 Winter Simulation Conference, WSC'06. WSC, pp. 398-405, 2006 Winter Simulation Conference, Monterey, United States, 3/12/06.

    Efficient Simulation of Population Overflow in Parallel Queues. / Nicola, V.F.; Zaburnenko, T.S.

    Proceedings of the 2006 Winter Simulation Conference, WSC'06. WSC, 2006. p. 398-405.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    TY - GEN

    T1 - Efficient Simulation of Population Overflow in Parallel Queues

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    AU - Zaburnenko, T.S.

    PY - 2006/12

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    N2 - In this paper we propose a state-dependent importance sampling heuristic to estimate the probability of population overflow in networks of parallel queues. This heuristic approximates the “optimal��? state-dependent change of measure without the need for dif��?cult mathematical analysis or costly optimization involved in adaptive methodologies. Comprehensive simulations of networks with an arbitrary number of parallel queues and different traf��?c intensities yield asymptotically ef��?cient estimates (with relative error increasing sub-linearly in the overflow level) where no other state-independent importance sampling techniques are known to be ef��?cient. The ef��?ciency of the proposed heuristic surpasses those based on adaptive importance sampling algorithms, yet it is easier to determine and implement and scales better for large networks.

    AB - In this paper we propose a state-dependent importance sampling heuristic to estimate the probability of population overflow in networks of parallel queues. This heuristic approximates the “optimal��? state-dependent change of measure without the need for dif��?cult mathematical analysis or costly optimization involved in adaptive methodologies. Comprehensive simulations of networks with an arbitrary number of parallel queues and different traf��?c intensities yield asymptotically ef��?cient estimates (with relative error increasing sub-linearly in the overflow level) where no other state-independent importance sampling techniques are known to be ef��?cient. The ef��?ciency of the proposed heuristic surpasses those based on adaptive importance sampling algorithms, yet it is easier to determine and implement and scales better for large networks.

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    KW - METIS-237909

    KW - IR-66871

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    BT - Proceedings of the 2006 Winter Simulation Conference, WSC'06

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    Nicola VF, Zaburnenko TS. Efficient Simulation of Population Overflow in Parallel Queues. In Proceedings of the 2006 Winter Simulation Conference, WSC'06. WSC. 2006. p. 398-405