A Reliable New Traffic Control Model Based on Fuzzy Neural Network
一种基于模糊神经网络的可靠流量控制模型

In this paper, we present a kind of congestion control model which based on fuzzy neural network(FNN)from the practical status of data buffer, for the sake of controlling P2P traffic.This model divides data buffer into two queues which store P2P data packets and non-P2P data packets respectively.It forcasts and evaluates conditions of buffer queues through FNN as well as guides space allocation of each queue through constructing a evaluation function. Thus,this model is able to control congestion condition of each queue and resize allocation of queues in the buffer automatically, then it can avoid lock-out of the buffer by actively dropping packets before the buffer is overflow.Results from simulation experiments show that this model has gained better effect in ensuring network resource allocation equitable, it can also decreases the delay of packet queuing and the dropping ratio.Thus,it improves the ability of routers in dealing with network congestion.