无线Mesh网络中基于萤火虫和粒子群优化的网关部署组合算法  

Gateway Deployment Combination Algorithm Based on Fireflies and Particle swarm Optimization in Wireless Mesh Network

作　　者：刘友武 LIU You-wu(School of Economics and Management,Sanming University,Sanming 365004,China)

机构地区：[1]三明学院经济与管理学院,福建三明365004

出　　处：《三明学院学报》2021年第3期15-22,共8页Journal of Sanming University

基　　金：福建省教育厅中青年教师教育科研项目(JAT190721);三明学院科学研究发展基金(B201934)。

摘　　要：针对无线Mesh网络多网关特征,从网关部署与网络性能平衡的角度出发,描述了网关部署与网关负载均衡的问题,提出一种基于萤火虫和粒子群优化的组合算法。首先,根据无线Mesh网络的拓扑结构,通过萤火虫算法确定网关数量;其次,在多目标的全局网络环境中利用遗传算法对全局进行优化;最后,通过粒子群优化算法实现网关数量的最小化和负载均衡的最优化。模拟的实验结果表明,CFPSO算法能够有效地优化负载均衡与网关数量问题,与基于单机调度问题的启发式算法、粒子群优化算法以及萤火虫算法相比,该算法能较好地平衡网关数量与负载均衡的关系,在QOS保证下有效提高了网关的有效荷载和数据投递率,并降低了端到端的延迟。Aiming at the characteristics of multi-gateway in Wireless Mesh Network(WMN), the problem of gateway deployment and gateway load balancing is described from the perspective of gateway deployment and network performance balance. A combination of firefly and particle swarm optimization(CFPSO) algorithm is proposed. First, according to the topological structure of wireless Mesh Network, the number of gateways is determined by firefly algorithm;secondly, the genetic algorithm is used to optimize the global situation in a multi-objective global network environment;finally, the number of gateways is minimized by the combination of firefly and swarm particles and optimization of load balancing. The simulated experimental results show that the CFPSO algorithm can effectively optimize the problem of load balancing and the number of gateways. Compared to the Heuristic algorithm based on Single Machine Scheduling, SMS, Particle Swarm Optimization, PSO algorithm, firefly algorithm, the algorithm can better balance the number of gateways and the balance of load balancing. Under the guarantee of QoS(Quality of Service), the effective load and data delivery rate of the gateway is effectively improved, and the end-to-end delay is reduced.

关 键 词：无线MESH网络 萤火虫算法 粒子群优化算法 网关节点 负载均衡 

分 类 号：TN929.5[电子电信—通信与信息系统]