智慧城市中无线网络节点部署优化方案研究  

Node Deployment Optimization of Wireless Network in Smart City

作　　者：黄书强[1] 王高才[2] 单志广[3] 邓玉辉[4] 李阳[4] 陈庆麟[5] 

机构地区：[1]暨南大学网络与教育技术中心,广州510632 [2]广西大学计算机与电子信息学院,南宁530004 [3]国家信息中心信息化研究部,北京100045 [4]暨南大学信息科学技术学院,广州510632 [5]华南理工大学自动化科学与工程学院,广州510641

出　　处：《计算机研究与发展》2014年第2期278-289,共12页Journal of Computer Research and Development

基　　金：国家自然科学基金项目(61063045;61262003;61272073;61373125);广东省自然科学基金重点项目(S2013020012865);广西自然科学杰出青年基金项目(2013GXNSFGA019006);广东省科技计划基金项目(2012B010100027;2012B091100161);2013年广州市科技计划基金项目(2013Y4300017);广东省教育厅科技创新基金项目(2013KJCX0018)

摘　　要：智慧城市无线网络基础设施中,网络节点部署直接影响到网络服务质量.该问题可归结为在给定的几何平面上部署合适的普通AP节点作为无线终端的访问节点,部署特殊节点作为网关以汇聚普通节点的流量到有线网络中.以无线Mesh网络为例,提出根据区域人流量的统计来确定AP节点的部署位置和数量,将网关节点部署问题抽象为几何K-中心问题.以节点和网关之间路径长度最小为优化目标,提出自适应的粒子群算法来求解网关节点部署位置.在自适应粒子群算法中引入随机调整惯性权重、自适应改变学习因子和邻域搜索等改进策略,并设计一种新的适值函数计算方法,使得算法更容易获得最优解.仿真结果表明,相对于GA算法和K-means算法,改进粒子群算法求解效果稳定,鲁棒性强,可获得更小的覆盖半径,从而提高网络的服务质量.In smart city, the deployment of network nodes of wireless networks has direct effect on network quality of service. This problem can be described as deploying appropriate AP as access nodes and special nodes as gateway nodes to aggregate traffic to Internet in a given geometric plane. In the paper, wireless mesh network as an example, number and deployment location of AP nodes can be determined by the regional flow of people statistics, and gateway nodes deployment is ed as a geometric K-center problem. To solve the geometric K-center problem, an improved adaptive PSO algorithm is proposed to optimize the minimum coverage radius. The fitness function is redesigned, and random inertia weight adjustment, adaptive learning factor, neighborhood searching strategy are introduced to the improved PSO to get wider solution. Compared with GA algorithm and K-means algorithm, simulation results show that the improved PSO algorithm is more stable and can get shorter path length, thus the network quality of service can be improved.

关 键 词：智慧城市 无线MESH网络 网关部署 几何K-中心 自适应粒子群算法 路径长度 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]