自适应逃逸粒子群算法的网络节点覆盖优化仿真  

Adaptive Escape Particle Swarm Algorithm of the Network Node Coverage Optimization Simulation

作　　者：刘伟[1] 崔永锋[1] 

机构地区：[1]周口师范学院计算机科学与技术学院,河南周口466001

出　　处：《微电子学与计算机》2013年第10期165-168,共4页Microelectronics & Computer

基　　金：河南省重点科技攻关项目(102102210265);河南省基础与前沿研究项目(132300410400);河南省信息技术教育研究规划项目(ITE12064)

摘　　要：研究无线传感器节点优化选择.传统LEACH分簇算法中,节点选择的随机性很大,没有很好地参考节点中的多个属性,通信的簇头分布也无规律,算法把能量消耗分摊到所有的节点上,一旦选择边沿节点作为簇头,一些节点必须经过长距离的路由转发才能到达簇头,造成通信效率较低.为了避免上述缺陷,提出了一种基于自适应逃逸粒子群算法的网络节点覆盖优化方法.建立自适应逃逸粒子群算法的数学模型,准确描述网络节点覆盖问题.利用自适应逃逸粒子群方法,计算无线传感网络节点最优位置,从而实现网络节点覆盖优化.实验结果表明,这种算法能够实现网络节点覆盖优化处理,从而提高无线传感网络数据传递的效率.Research of wireless sensor node optimization choice. LEACH traditional clustering algorithm, the nodes choose the randomness is very big, not very good reference node of the multiple attribute, the communication of the cluster head distribution is also disordered, the algorithm the energy consumption apportioned to all the nodes, once selected edge node as the cluster head, some node must go through a long routing forward to get to cluster head, cause communication low efficiency. In order to avoid the defect, the article puts forward a method based on adaptive escape particle swarm algorithm of the network node coverage optimization method. Establish adaptive escape particle swarm optimization mathematical model, accurately described network node covering problems. Using adaptive escape particle swarm method, calculation of wireless sensor network node optimal position, so as to realize the network node coverage optimization. The experimental results show that this algorithm can realize network node coverage optimization processing, so as to improve the wireless sensor network data transmission efficiency.

关 键 词：自适应逃逸粒子群 网络覆盖率 无线传感网络 

分 类 号：F127[经济管理—世界经济]