A class of Active Queue Management algorithm based on BP neural network

As an end-to-end congestion control mechanism, Active Queue Management (AQM) technology maintains smaller queue length and higher link utilization through discarding packets in intermediate network nodes. This paper discussed some previous AQM algorithms, RED, BLUE and RLGD, and found out shortcomings in which by comparing with them. On the Basis of Artificial Intelligence (AI) theory and technology, a new AQM algorithm based on BP neural network is proposed. In the end, the implement of the new Active Queue Management algorithm is presented, and the convergence is proved.