Connection admission control of ATM network using integrated MLP and fuzzy controllers

This paper presents a new approach to the problem of call admission control (CAC) of variable bit rate (VBR) trac in an asynchronous transfer mode (ATM) network. Our approach employs an integrated neural network and fuzzy controller to implement the CAC controller. This scheme capitalizes on the learning ability of a neural network and the robustness of a fuzzy controller. Experiments show that this scheme is able to achieve high throughput and low cell loss while achieving fairness among di€erent classes of VBR trac. For comparison, we have also implemented four other CAC schemes: (1) peak bandwidth method, (2) equivalent bandwidth method, (3) average bandwidth method and (4) neural network quality of service (QoS) predictor. Results of these experiments are presented in this paper. Ó 2000 Elsevier Science B.V. All rights reserved.