Self-aware networks and quality of service

    Authors

    E. Gelenbe;A. Nunez

    Keywords

    RANDOM NEURAL-NETWORK; ATM; Computer Science, Artificial Intelligence; Computer Science, Theory &; Methods

    Abstract

    We show how "self-awareness", through on-line self-monitoring and measurement, coupled with intelligent adaptive behaviour in response to observed data, can be used to offer quality of service to network users. We first describe the general principles which govern our design, and briefly describe the experimental packet network system we have built in which users are allowed to specify their QoS objectives. The network uses on-line adaptive traffic routing to try to meet the users' QoS requests. Cognitive or smart packets are used for self-observation, and reinforcement learning with neural networks is implemented at network nodes to seek new paths and deduce improved paths from existing routes. First we show how the network is able to discover routes, beginning with an "empty state" and starting from a random search. Secondly we show how our network can intelligently direct traffic through the Internet to optimize web traffic for a user by offering the best quality of service through different Internet Service Providers.

    Journal Title

    Artificail Neural Networks and Neural Information Processing - Ican/Iconip 2003

    Volume

    2714

    Publication Date

    1-1-2003

    Document Type

    Article

    Language

    English

    First Page

    901

    Last Page

    908

    WOS Identifier

    WOS:000185378100107

    ISSN

    0302-9743; 3-540-40408-2

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