Abstract
This paper deals with a novel buffer management scheme based on evolutionary computing for shared-memory ATM switches. The philosophy behind it is adaptation of the threshold for each output logical queue to the real traffic conditions by means of a system of fuzzy inferences. The optimal fuzzy system is achieved using a systematic methodology based on genetic algorithms for membership-function selecting and tuning. This methodology approach allows the fuzzy system parameters to be automatically derived when the switch parameters vary, offering a high degree of scalability to the fuzzy control system. Its performance is very close to that of an ideal mechanism like the push-out mechanism, and at any rate much better than that of the threshold schemes based on conventional logic. In addition it is simple to implement and above all inexpensive when implemented using VLSI technology.
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