An integrated fuzzy-GA approach for buffer management
This paper deals with a novel buffer management scheme based on evolutionary computing
for shared-memory asynchronous transfer mode (ATM) switches. The philosophy behind it is
adaptation of the threshold for each logical output 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 (GAs), which allows the fuzzy system
parameters to be derived for each switch size, offering a high degree of scalability to the …
for shared-memory asynchronous transfer mode (ATM) switches. The philosophy behind it is
adaptation of the threshold for each logical output 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 (GAs), which allows the fuzzy system
parameters to be derived for each switch size, offering a high degree of scalability to the …
This paper deals with a novel buffer management scheme based on evolutionary computing for shared-memory asynchronous transfer mode (ATM) switches. The philosophy behind it is adaptation of the threshold for each logical output 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 (GAs), which allows the fuzzy system parameters to be derived for each switch size, offering a high degree of scalability to the fuzzy control system. Its performance is comparable to that of the push-out (PO) mechanism, which can be considered ideal from a performance viewpoint, and at any rate much better than that of threshold schemes based on conventional logic. In addition, the fuzzy threshold (FT) scheme is simple and cost-effective when implemented using VLSI technology
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