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ATM congestion control using a fuzzy neural network

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2 Author(s)
A. Kwok ; TRLabs-Winnipeg, Man., Canada ; R. McLeod

This paper presents a new mechanism to control the link-by-link traffic of an asynchronous transfer mode (ATM) switch. This method makes use of the linguistic ability of fuzzy set theory and logic to handle the complexity. A fuzzy neural network (FNN) will learn to control the injection rate of the previous ATM switch by issuing a signal. The FNN will learn to follow the inference method, and decide what kind of signal should be sent based on a set of rules as in the inference method

Published in:

Electrical and Computer Engineering, 1996. Canadian Conference on  (Volume:2 )

Date of Conference:

26-29 May 1996