Applying Fuzzy Sliding Mode Control Based on Genetic Algorithms to Congestion Avoidance in Computer Network
نویسندگان
چکیده
of Fuzzy Sliding Mode Control (FSMC) based on Genetic Algorithms (GAs) roposed control strategy, a robust controller is designed for Active Queue n computer networks. AQM takes a trade-off between link utilization and ata packets. From control point of view, it is rational to regard AQM as a m. We design a fuzzy sliding mode controller for the AQM system as an nd apply the optimal searching algorithms and GAs to find the optimal rules ions of the FSMC. Some computer simulations are provided to show the posed control action. Simulation results show the FSMC based on GAs has that of SMC and FSMC in providing efficient queue management. l; sliding mode control, congestion control, computer networks l mechanism, while necessary and powerful, are not sufficient to provide mstances, specially with the rapid growth in size and the strong requirements (QoS) support, because there is a limit to how much control can be stem. It is needed to implement some measures in the intermediate nodes to stem congestion avoidance mechanisms. Active Queue Management (AQM), ropping/marking mechanism in the router queue, has been recently proposed d congestion control in the Internet [1,2]. tioned that, even for the present Internet architecture, network congestion cal and high priority issue, and is unlikely to disappear in the near future. sider the current utilization trends, congestion in the Internet maybe come ffective, robust, and efficient methods for congestion control are developed. sting congestion control solutions for TCP transported traffic [3] are ineffective, and it is generally accepted that these solutions cannot easily ous proposed ‘‘fixes’’ [4,5], new approaches [6], and architectures [7]. The emes employed by the TCP/IP protocol have been widely studied. The tecture is based on a connectionless, best-effort, end-to-end packet service CP is an end-to-end transport protocol that provides reliable, in-order service
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