“…The proposed fuzzy logic controller is aimed to overcome this disadvantage. In recent years, fuzzy logic controllers, especially FPI controllers, have been widely used for process control owing to their heuristic nature associated with simplicity and effectiveness for both linear and nonlinear systems [26]- [28]. In fact, for single-input single-output systems, fuzzy logic controllers can be essentially seen as PI type associated with nonlinear gain.…”
Re, G. and Urso, A. (2003) A genetic algorithm for the design of a fuzzy controller for active queue management. IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), 33 (3). pp. 313-324.
“…The proposed fuzzy logic controller is aimed to overcome this disadvantage. In recent years, fuzzy logic controllers, especially FPI controllers, have been widely used for process control owing to their heuristic nature associated with simplicity and effectiveness for both linear and nonlinear systems [26]- [28]. In fact, for single-input single-output systems, fuzzy logic controllers can be essentially seen as PI type associated with nonlinear gain.…”
Re, G. and Urso, A. (2003) A genetic algorithm for the design of a fuzzy controller for active queue management. IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), 33 (3). pp. 313-324.
“…In [1] , it was also argued that instead of basing cell discarding on the number of active sources and dividing the traffic load into three levels of threshold, it would have been better to let the threshold vary dynamically based on the cell arrival rate of each sources, since active sources may not generate enough cells to full the better at successive transmission cycles. Also in [3] , the switch resources (Buffer size and Bandwidth) are reserved for high priority traffic to generate the required QoS and a fuzzy priority control device at the input decide whether or not to accept or reject any new low priority cells, and the discarding of low priority cells already in the buffer is not allowed.…”
This study presents a technique for improving the quality of service (QoS ) guarantee in an ATM network. In the proposed model, it was assumed that high priority traffic have been allocated a switch resource to guarantee a given QoS and low priority cells are allowed to enter the buffer, to improve the exploitation of reserved resources. The proposed technique was backed up with an exact analytical model for evaluating the cell loss probability of high and low priority cells. The performance of the proposed model was evaluated using C++ programming language. The results of the simulation shows that the loss probability of both high and low cells reduces as the buffer capacity increase and that the performance of high priority cell is better than that of low priority cell
“…Ascia et al [3] propose a fuzzy priority control (FPC) buffer management scheme for ATM and IP networks. By reserving some switch resources (i.e.…”
Section: Ontrib U Tion and R Esu Ltsmentioning
confidence: 99%
“…A-REED [7] is a improved random early detection (RED) buffer management scheme for real-time traffic flows, which concerns with high throughput and utilization. FPC [3] is PBS-based buffer manage ment scheme, which achieves low high-priority packet loss rate, high utilization and high throughput. The buffer management unit is used to control connection admission and memory allocation to packets.…”
Section: Ontrib U Tion and R Esu Ltsmentioning
confidence: 99%
“…3 shows the status (including ConnectionsManager, available memory and remaining memory for new connection admission) after the connection m is canceled.In this figure, the connection m is removed from BEList in the ConnectionsManager, its connection queue is cleared and its occupied memory is released, available memory increases by the size of the released memory, and remaining memory for new connec tion admission increases by the size of the admission requirement of connection m .…”
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