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Chance-constrained stochastic programming forintegrated services network management

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  • E. Medova

Abstract

The design, dimensioning and traffic management of an Asynchronous Transfer Mode(ATM) network may be modelled as a hierarchical planning problem at different time-scales - capacity provision/expansion with intervals of weeks or months and real-time call routingat the time scale of the connection, which is itself treated in hierarchical order of transmittingcalls (sec), bursts (msec) or cells (msec). Taking the network topology as given, a chance-constrainedstochastic programme for integrated services network dimensioning and trafficmanagement is formulated using Hui's notion of effective bandwidth. This allows the removalof probabilistic constraints at the call level and leads to consideration of the networkmanagement problem as a linear deterministic multicommodity flow problem. To allowflexibility and easy problem formulation with various objectives and network specificationsthe decision support tool MODLER is employed. The model described can be used for aprototype software system for future network design and management. Copyright Kluwer Academic Publishers 1998

Suggested Citation

  • E. Medova, 1998. "Chance-constrained stochastic programming forintegrated services network management," Annals of Operations Research, Springer, vol. 81(0), pages 213-230, June.
    • Handle: RePEc:spr:annopr:v:81:y:1998:i:0:p:213-230:10.1023/a:1018901022726
    DOI: 10.1023/A:1018901022726
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    Cited by:

    1. M Riis & A J V Skriver & S F Møller, 2005. "Internet protocol network design with uncertain demand," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(10), pages 1184-1195, October.
    2. Morten Riis & Kim Allan Andersen, 2002. "Capacitated Network Design with Uncertain Demand," INFORMS Journal on Computing, INFORMS, vol. 14(3), pages 247-260, August.
    3. Alminana, Marc & Escudero, Laureano F. & Monge, Juan F. & Sanchez-Soriano, Joaquin, 2007. "On the enrouting protocol problem under uncertainty," European Journal of Operational Research, Elsevier, vol. 181(2), pages 887-902, September.

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