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计算机工程 ›› 2009, Vol. 35 ›› Issue (11): 205-206,. doi: 10.3969/j.issn.1000-3428.2009.11.070

• 人工智能及识别技术 • 上一篇    下一篇

基于信息熵多种群遗传算法的组播路由

岳承君1,尹凤杰1,井元伟2   

  1. (1. 辽宁大学信息学院,沈阳 110036;2. 东北大学信息科学与工程学院,沈阳 110004)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2009-06-05 发布日期:2009-06-05

Multicast Routing Based on Information Entropy Multi-population Genetic Algorithm

YUE Cheng-jun1, YIN Feng-jie1, JING Yuan-wei2   

  1. (1. School of Information, Liaoning University, Shenyang 110036; 2. School of Information Science and Engineering, Northeastern University, Shenyang 110004)
  • Received:1900-01-01 Revised:1900-01-01 Online:2009-06-05 Published:2009-06-05

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

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)

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