Abstract:
Taking account of the uncertain information and the unbalance of link results in the congestion of network, a Genetic Algorithm(GA) with the information entropy is presented to solve the problem in the multicast routing. The algorithm begins from a least-delay tree, searches the max information entropy multicast tree in the multi-population, and gets final multicast tree satisfying delay constraint and the least balance. The results show that the proposed algorithm performs better in terms of delaying a running time against existing heuristics algorithm, and constructs optimal delay-constrained and balance multicast tree efficiently.
Key words:
multicast routing,
information entropy,
multi-population Genetic Algorithm(GA)
摘要: 针对网络信息不确定性和链路负载不均匀所造成的网络拥塞,提出基于信息熵的组播路由算法。该遗传算法从最小代价树开始,在多种群中不断选择信息熵较大的种群,以求得满足延时要求且路径负载较小的组播树。结果表明,该算法性能快速、有效地构造最小时延组播树,且保证网络负载均衡分布。
关键词:
组播路由,
信息熵,
多种群遗传算法
CLC Number:
YUE Cheng-jun; YIN Feng-jie; JING Yuan-wei. Multicast Routing Based on Information Entropy Multi-population Genetic Algorithm[J]. Computer Engineering, 2009, 35(11): 205-206,.
岳承君;尹凤杰;井元伟. 基于信息熵多种群遗传算法的组播路由[J]. 计算机工程, 2009, 35(11): 205-206,.