Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Fuzzy logic, neural networks, and soft computing
Communications of the ACM
IEEE/ACM Transactions on Networking (TON)
Dynamic queue length thresholds for shared-memory packet switches
IEEE/ACM Transactions on Networking (TON)
Optimal buffer management policies for shared-buffer ATM switches
IEEE/ACM Transactions on Networking (TON)
Scalable Hardware Priority Queue Architectures for High-Speed Packet Switches
IEEE Transactions on Computers
An adaptive fuzzy threshold scheme for high performance shared-memory switches
Proceedings of the 2001 ACM symposium on Applied computing
Analysis of the parallel packet switch architecture
IEEE/ACM Transactions on Networking (TON)
INFOCOM '95 Proceedings of the Fourteenth Annual Joint Conference of the IEEE Computer and Communication Societies (Vol. 1)-Volume - Volume 1
VLSI hardware architecture for complex fuzzy systems
IEEE Transactions on Fuzzy Systems
IEEE Journal on Selected Areas in Communications
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This paper deals with a novel buffer management scheme based on the combination of evolutionary computing and fuzzy logic for shared-memory packet 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 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 close to that of the push-out 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 scheme is simple to implement, unlike the push-out mechanism which is not practically feasible in high-speed switches due to the amount of time required for computation, and above all inexpensive when implemented using current standard technology.