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)
59 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
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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

Y1 - 2006/12

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.

KW - EWI-9066

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