| 摘要: |
| 以ATM(asynchronoustransfermode)为研究对象,提出一种基于模糊神经网络(fuzzyneuralnetwork，简称FNN)的流量预测和拥塞控制策略.拥塞控制是高速网络(如ATM)研究中的关键问题之一.传统的基于BP神经网络的流量预测方法因其收敛速度较慢且具有较大的误差,影响了拥塞控制效果,而模糊神经网络由于具有处理不确定性问题和很强的学习能力,能很好地解决这一问题.最后通过仿真,比较和分析了基于BP神经网络和基于FNN方法的性能,证明此方法是有效的. |
| 关键词: 拥塞控制 流量预测 模糊神经网络 高速网 络 ATM(asynchronous transfer mode) |
| DOI： |
| 分类号: |
| 基金项目:国家重点基础研究发展规划资助项目(G1998030405) |
|
| Policy of Fuzzy Neural Network Based Congestion Control in High- Speed Network |
|
HE Xiao-yan,WU Jie-yi,GU Guan-qun
|
| Abstract: |
| In this paper, a kind of traffic prediction a nd 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 fo r congestion control using BPN (back propagation neural network) has suffered fr om long convergence time and dissatisfying precision, and it is not effective. T he fuzzy neural network scheme presented in this paper can solve these limitatio ns satisfactorily for its good capability of processing inaccurate information a nd learning. Finally, the performance of the scheme based on BPN is compared wit h the scheme based on FNN using simulations. The results show that the FNN schem e is effective. |
| Key words: congestion control tr affic prediction fuzzy neural network high-speed network ATM (asynchronous transfer mode) |
