Policy of Fuzzy Neural Network Based Congestion Control in High-Speed Network
Xiaoyan He · 2001
In this paper, a kind of traffic prediction and congestion control policy based on FNN (fuzzy neural network) is proposed for ATM (asynchronous transfer mode). Congestion control is one of the key problems in high-speed networks, such as ATM. Conventional traffic prediction method for congestion control using BPN (back propagation neural network) has suffered from long convergence time and dissatisfying precision, and it is not effective. The fuzzy neural network scheme presented in this paper can solve these limitations satisfactorily for its good capability of processing inaccurate information and learning. Finally, the performance of the scheme based on BPN is compared with the scheme based on FNN using simulations. The results show that the FNN scheme is effective.