Energy-saving Coverage Algorithm for Wireless Sensor Network Based on Co-evolutionary Particle Swarm Optimization

摘要:

针对当前无线传感器网络覆盖算法存在能耗较高、节点大量冗余的缺陷,提出一种基于协同进化粒子群算法的WSN节能优化覆盖算法.以WSN的网络覆盖率、剩余能量和冗余程度为优化目标,建立粒子群优化模型.采用遗传算法的交叉变异算子,加强算法寻优能力.仿真结果表明,新的算法在提高能量利用效率的同时维护了良好的网络覆盖率,有效延长了网络生命周期,达到了节能优化覆盖的目标.

To solve the problem that the most covering algorithm of wireless sensor network has the weakness of serious energy consumption and lots of redundant nodes. We proposed an energy-conservation optimization covering algorithm which based on co-evolutionary particle swarm optimization（PSO）. We constructed the PSO model according to the ratio of the net- work coverage, residual energy and the degree of redundant. The mutation and crossover Operator of genetic algorithm was a- dopted to enhance the searching able of the proposed algorithm. The simulation results indicate that the proposed algorithm can improve energy efficiency, maintain a good network coverage rate, effectively prolong the lifetime of network and achieves the goal of energy-saving optimization covering.

作者:

王长清 黄静

机构地区:

betway官方app 物理与电子工程学院

出处:

《betway官方app 学报：自然科学版》 CAS 北大核心 2016年第1期54-58,共5页

基金:

河南省重点科技攻关项目(122102310483)

关键词:

无线传感器网络 粒子群算法 优化覆盖 遗传算法 节能

Wireless Sensor Network particle swarm optimization optimization covering energy-conserving

分类号:

TP393 [自动化与计算机技术—计算机应用技术]

基于协同进化粒子群算法的无线传感器网络节能优化覆盖算法.pdf