摘要
针对具有多个不相关可加度量的QoS组播路由问题,提出基于混沌控制量的QoS组播路由算法。该算法通过对神经元的内部状态施加一个混沌控制量,可以有效控制神经网络的能量函数增加、减少或保持不变,避免陷入局部最小点。计算机仿真结果表明,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,与其他启发式算法相比,适用于带有较少目的结点的大规模网络。
This paper presentes a new algorithm based on chaotic controlled quantities to optimize the multicast tree with delay bound. The proposed Chaotic Neural Network（CNN） can control network energy to increase, decrease or keep unchanged through chaotic controlled quantities added to each neuron, which can help neural network to enlarge searching space to get optimal solutions and avoid local minima or invalid solutions. The energy function is also defined to represent the cost of optimal path with the delay bound. Comparing the results with the other algorithms, results show that the proposed algorithm is both efficient and effective in constructing the optimal delay bound multicast tree.
出处
《计算机工程》
CAS
CSCD
北大核心
2008年第9期130-132,共3页
Computer Engineering
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)
关键词
混沌神经网络
计算机网络
组播路由
Chaotic Neural Network （CNN）
computer network
multicast routing
