首页> 外文会议>International Conference on Advanced Technologies for Communications >A Solution to Select Multicast Service Nodes of Hierarchical Overlay Multicast Tree Based on Immune Evolution
【24h】

A Solution to Select Multicast Service Nodes of Hierarchical Overlay Multicast Tree Based on Immune Evolution

机译:基于免疫演化的分层覆盖多播树选择组播服务节点的解决方案

获取原文

摘要

For the reliable real time video transmission of overlay network, optimal multicast service nodes (MSNs) should be selected to build highly efficient hierarchical overlay multicast tree. In this paper, a MSNs selection algorithm based on immune evolution is proposed. MSNs are encoded by real-coded mechanism, and the K-medoids clustering distance is used to measure the similarity between MSN and other nodes. In accordance with the actual characteristics of MSN, a fitness function including penalty factor is brought forward to prevent undesirable individuals participating in evolution. Also, on the base of SGA, immune vaccines are extracted and imported into the evolutionary population to improve the global optimizing capability of algorithm. Theoretical analysis and simulation results show that this algorithm is effective and feasible. As to select MSNs, it not only overcomes the imitation-sensitive problem and local convergence caused by the traditional K-medoids algorithm but also avoid degradation phenomenon appeared in standard genetic algorithm , and improve search capabilities and speed convergence.
机译:对于覆盖网络的可靠实时视频传输,应选择最佳多播服务节点(MSN)以构建高效的分层覆盖多播树。本文提出了一种基于免疫演化的MSNS选择算法。 MSN由实际编码机制编码,K-METOIDS聚类距离用于测量MSN和其他节点之间的相似性。根据MSN的实际特征,提出了一种适应性函数,包括惩罚因子,以防止不受欢迎的个人参与演变。此外,在SGA的基础上,提取免疫疫苗并进口到进化人群中,以改善算法的全球优化能力。理论分析和仿真结果表明,该算法是有效可行的。为了选择MSN,它不仅克服了由传统的K-METOIDS算法引起的模仿敏感问题和局部收敛,还避免了标准遗传算法中出现的降级现象,并改善了搜索能力和速度收敛。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号