Please use this identifier to cite or link to this item: https://doi.org/10.1016/S1389-1286(99)00124-3
Title: Connection admission control of ATM network using integrated MLP and fuzzy controllers
Authors: Ng, N.O.L.
Tham, C.K. 
Issue Date: Jan-2000
Source: Ng, N.O.L., Tham, C.K. (2000-01). Connection admission control of ATM network using integrated MLP and fuzzy controllers. Computer Networks 32 (1) : 61-79. ScholarBank@NUS Repository. https://doi.org/10.1016/S1389-1286(99)00124-3
Abstract: This paper presents a new approach to the problem of call admission control (CAC) of variable bit rate (VBR) traffic 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 different classes of VBR traffic. 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.
Source Title: Computer Networks
URI: http://scholarbank.nus.edu.sg/handle/10635/61961
ISSN: 13891286
DOI: 10.1016/S1389-1286(99)00124-3
Appears in Collections:Staff Publications

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