Genetic and Particle Swarm Hybrid QoS Anycast Routing Algorithm

被引：1
|
作者：
Li Taoshen [1 ]
Xiong Qin [1 ]
Ge Zhihui [1 ]
机构：
[1] Guangxi Univ, Sch Comp Elect & Informat, Nanning 530004, Peoples R China
来源：
2009 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND INTELLIGENT SYSTEMS, PROCEEDINGS, VOL 1 | 2009年
关键词：
anycast routing; genetic algorithm; particle swarm optimization; quality of service(QoS);
D O I：
10.1109/ICICISYS.2009.5357837
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Anycast is proposed in IPv6 as a new communication model and becoming increasingly important Anycast refers to the transmission of data from a source node to (any) one member in the group of designed recipients in a network The QoS anycast routing problem is a nonlinear combination optimization problem, which is proved to be a NP complete problem A hybrid algorithm which combines genetic algorithm and particle swarm optimization algorithm is proposed to solve anycast routing problem with multiple QoS constraints The algorithm uses an update operator to solve the problem which the routing paths can learn from other bester paths, so that whole population tends to the best path progressively The simulation results show that our algorithm can overcome the disadvantages of genetic algorithm and particle swarm optimization algorithm, and achieve better QoS performance It has faster convergence speed and can escape from local optimum
引用
收藏
页码：313 / 317
页数：5
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