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Hierarchical neuro-fuzzy call admission controller for ATM networks

✍ Scribed by A Chatovich; S Oktuğ; G Dündar


Publisher
Elsevier Science
Year
2001
Tongue
English
Weight
271 KB
Volume
24
Category
Article
ISSN
0140-3664

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✦ Synopsis


In this work, a hierarchical neuro-fuzzy call admission controller for ATM networks based on the GARIC architecture is proposed. The controller contains a neural network as a critic, using the reinforcement learning scheme, and three fuzzy sub-networks, controlling cell loss ratio, queue size and link utilization in the ATM multiplexer. The ®nal decision of the call admission controller is obtained as a weighted combination of the decisions generated by the fuzzy sub-networks. In order to study the performance of the proposed controller, it is simulated under various variable bit rate traf®c patterns and the results obtained are evaluated in terms of network utilization. Introduction of an initial knowledge base to improve training times is discussed and the results with and without the knowledge base are given. Finally, methods to enhance the performance of the proposed controller are mentioned.


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