Network congestion avoidance strategy with particle filter

Based on the property of Markov chain for network data, a new estimator with particle filter is proposed for congestion control in this paper. The proposed scheme can predict the traffic patterns by the decision-making model. Compared with previous scheme based on fuzzy neural network, the proposed scheme can adaptively adjust the network rate in real-time and reduce the cell loss rate, so that it can efficiently avoid the traffic congestion. Simulation results are shown to be promising.