Abstract

Active queue management (AQM) has been widely used for congestion avoidance in transmission control protocol (TCP) networks. Although numerous AQM schemes have been proposed to regulate a queue size close to a reference level, most of them are incapable of adequately adapting to TCP network dynamics due to TCP's non-linearity and time-varying stochastic properties. To alleviate these problems, we propose a novel adaptive AQM(active queue management ) algorithm for TCP network to cope with the network delay and time-varying network parameters based on RBF-PID controller, the RBF(redial basis function) neural network is employed to automatically tune the controller's parameters according to link capacity, traffic load and transmitting time-delay, which makes the presented AQM algorithm perform well for a wide-range of network conditions. The simulation results have shown that the RBF-PID-based AQM is feasible and efficient, and yields superior performance with faster transient time and better adaptive ability compared to the proportional-integral (PI)-based AQM.

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