改进的聚合组播算法  

Advanced aggregated multicast algorithm

作　　者：徐剑[1,2] 倪宏[2] 邓浩江[2] 刘磊[2] 

机构地区：[1]中国科学院大学,北京100049 [2]中国科学院声学研究所国家网络新媒体工程技术研究中心,北京100190

出　　处：《计算机应用研究》2013年第10期3048-3050,3056,共4页Application Research of Computers

基　　金：国家“863”计划基金资助项目(2011AA01A102);中国科学院战略性先导科技专项子课题资助项目(XDA06010302)

摘　　要：针对组播状态可扩展性问题进行研究,提出了一种改进的聚合组播算法。该算法在动态在线聚合组播算法的基础上,确定匹配时可行的聚合树范围,以减少匹配和计算次数,降低时间复杂度;改进最优匹配聚合树的选择算法,并对网络中聚合树进行定期调整,以优化聚合树结构,去掉不必要的中间节点,提高聚合度,降低节点转发状态。仿真实验表明,与同类算法相比,该算法能够以较低的时间复杂度,取得较高的聚合度和转发状态降低率,在并发组播组数目较高和组密度较高时效果更加明显。In order to improve muhicast state scalability problem, this paper proposed an advanced aggregated multicast algo- rithm. The algorithm was on the basis of generic dynamic on-line algorithm. When matching group-tree, the algorithm deter- mined the feasible range of aggregated trees to reduce matching and calculation times and to get lower time complexity. In or- der to optimize aggregated tree structure, remove unnecessary intermediate node, increase aggregated degree and reduce node forwarding state, the algorithm improved the optimal matching aggregated tree selection algorithm and regularly adjusted aggre- gation tree in the network. Simulation results show that, when compared to similar algorithm, the algorithm can get higher ag- gregated degree and state reduction ratio in lower time complexity, and the improvement is much more obviously in the higher number of concurrent multicast group and group density.

关 键 词：组播状态可扩展性 聚合组播 聚合树 优化 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]