基于混沌神经网络的QoS组播路由算法  

QoS-based Multicast Routing Algorithm Based on Chaotic Neural Network

作　　者：张慧档[1] 吕娜 贺昱曜[1] 徐浩翔[2] 

机构地区：[1]西北工业大学航海学院,陕西西安710072 [2]空军工程大学科研部,陕西西安710051

出　　处：《空军工程大学学报（自然科学版）》2008年第1期70-73,共4页Journal of Air Force Engineering University(Natural Science Edition)

基　　金：全国优秀博士学位论文作者专项资金资助项目(200250);河南省自然科学基金资助项目(411012400)

摘　　要：为了改变Hopfield网络的能量函数梯度下降的趋势,对神经元的内部状态施加了一个混沌控制量以控制神经网络的能量函数增加,减少或保持不变。将该混沌神经网络应用于解决QoS组播路由问题,提出了基于该混沌神经网络的QoS组播路由算法。通过计算机仿真,该算法能根据组播应用对费用和时延的要求,快速有效地构造组播树,与当前其它启发式算法相比较,本文提出的算法是可行和有效的。This paper presents a chaotic neural network （CNN） model through adding chaotic control quantities to each neuron. The chaotic control quantities are used to control the neural network energy function increasing, decreasing or keeping unchanged which can help the neural network to enlarge searching space to get optimal solutions and avoid local minima or invalid solutions. In order to study the delay bound and the least cost multicast routing problem, a new algorithm based on CNN is proposed to optimize the multicast tree with delay bound, and the energy function is defined to represent the cost of optimal path with the delay bound. Through the comparative simulation with other algorithms, the results show that the proposed algorithm is both efficient and feasible in constructing the optimal delay bound multicast tree.

关 键 词：混沌神经网络 QOS 组播路由 暂态混沌 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]