An Improved Random Early Detection Algorithm Based on Flow Prediction
Random Early Detection(RED) is a network congestion control algorithm which calculates the packet-lossratio according to current length of average queue. This paper describes an improved RED algorithm: Firstly, predicts network flows with RBF neural Network in order to forecast queue length much earlier, and then, fits the Packet-loss-ratio of RED algorithm according to some special points using curve fitting method, therefore, controls nonlinear network congestion. From our simulation, it can be concluded that the algorithm avoids congestion more efficiently.