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DOI:
Journal of Software:2001.12(1):41-48

一种基于FNN的高速网络拥塞控制策略
何小燕,吴介一,顾冠群
(教育部 计算机网络和信息集成重点实验室,江苏 南京  210096,东南大学 计算机科学与工程系,江苏 南京 210096)
Policy of Fuzzy Neural Network Based Congestion Control in High- Speed Network
HE Xiao-yan,WU Jie-yi,GU Guan-qun
()
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Received:November 15, 1999    Revised:January 25, 2000
> 中文摘要: 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.
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.
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基金项目:国家重点基础研究发展规划资助项目(G1998030405) 国家重点基础研究发展规划资助项目(G1998030405)
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何小燕,吴介一,顾冠群.一种基于FNN的高速网络拥塞控制策略.软件学报,2001,12(1):41-48

HE Xiao-yan,WU Jie-yi,GU Guan-qun.Policy of Fuzzy Neural Network Based Congestion Control in High- Speed Network.Journal of Software,2001,12(1):41-48