遗传算法在聚合组播问题优化中的应用  

Application of genetic algorithm in aggregated multicast optimization

作　　者：王进科[1] 王华[1] 

机构地区：[1]山东大学计算机科学与技术学院,济南250101

出　　处：《计算机工程与应用》2009年第5期82-85,146,共5页Computer Engineering and Applications

基　　金：国家自然科学基金(No.60773101)~~

摘　　要：IP组播至今仍没有在Internet上被广泛应用,其中一个重要原因是组播转发状态的扩展性问题。聚合组播是一种减少组播转发状态的新技术,其主要目标是使网络中能够复合的组播组共用一棵组播分发树,从而减少转发状态,提高网络性能。采用遗传算法求解聚合组播问题。仿真结果表明,该算法对聚合组播问题有巨大的优化作用。IP muhicast is not widely deployed yet over Internet.One of the important reasons is the scalability problem of the muhicast forwarding states.Aggregated muhicast is a new technology to reduce muhicast forwarding states,which aims to force multiple groups to share a single distribution muhicast tree,so as to reduce the number of trees in the network,consequently, forwarding state is reduced,and thus the performance of muhicast network can be improved.This paper utilizes genetic algorithm to solve aggregated muhicast.The simulation results show that this algorithm has a great effect on the aggregated performance.

关 键 词：聚合组播 最小集合覆盖 遗传算法 熔合操作 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]