This paper is concerned with dynamic resource allocation in ATM networks. One of the essential issues in designing and configuring an ATM network is guaranteeing the quality of service for different connections. This needs more advanced functions to monitor the current situation, determine the requi
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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