Neural network approach to multicast routing in real-time communication networks

Chotipat Pornavalai, Goutam Chakraborty, Norio Shiratori

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

    31 Citations (Scopus)

    Abstract

    Real-time communication networks are designed mainly to support multimedia applications, especially the interactive ones, which require a guarantee of Quality of Service (QoS). Moreover, Multicasting is needed as there are usually more than two peers who communicate together using multimedia applications. As for the routing, network has to find an optimum (least cost) multicast route, that has enough resources to provide or guarantee the required QoS. This problem is called QoS constrained multicast routing and was proved to be NP-complete problem. In contrast to the existing heuristic approaches, in this paper we propose a modified version of Hopfield neural network model to solve QoS (delay) constrained multicast routing. By the massive parallel computations of neural network, it can find near optimal multicast route very fast, when implemented by hardware. Simulation results show that the proposed model has the performance near to optimal solution and comparable to existing heuristics.

    Original languageEnglish
    Title of host publicationInternational Conference on Network Protocols
    Place of PublicationLos Alamitos, CA, United States
    PublisherIEEE
    Pages332-339
    Number of pages8
    Publication statusPublished - 1995
    EventProceedings of the 1995 International Conference on Network Protocols - Tokyo, Jpn
    Duration: 1995 Nov 71995 Nov 10

    Other

    OtherProceedings of the 1995 International Conference on Network Protocols
    CityTokyo, Jpn
    Period95/11/795/11/10

    ASJC Scopus subject areas

    • Software

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