ROUTING STRATEGY BASED ON MULTI-AGENT SYSTEMS AND NEURAL NETWORK
基于多Agent系统和神经网络的路由选择策略

In mainland China, long distance telecommunications network's switch and link usage rates are only about 45% and 30%~40%, respectively. It is estimated that raising one percent of switch rate of the current network will result in revenue almost one billion RMB. In the paper, by analysing the demerit of routing schemes being used, a new intelligent routing strategy based on multi-agent systems and neural network forecasting is presented, including network model, routing procedure, and agent connotation depiction. Meanwhile, recurrent neural network forecasting is introduced. Simulation demonstrates it is outstanding by virtue of distribution and intelligence. Hence it provides an excellent way to improve switch rate and balance of network load.