| 基于量子粒子群优化算法的无线传感器网络节点优化 |
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| 引用本文： | 王艳萍,张惠敏,刘新贵. 基于量子粒子群优化算法的无线传感器网络节点优化[J]. 传感器与微系统, 2010, 29(2) |
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| 作者姓名： | 王艳萍 张惠敏 刘新贵 |
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| 作者单位： | 1. 郑州铁路职业技术学院信息工程系,河南,郑州,450052
2. 解放军信息工程大学测绘学院,河南,郑州,450052 |
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| 摘 要： | 针对无线传感器网络感知节点的分布优化问题进行了研究,提出了一种基于量子粒子群优化(QPSO)算法的分布优化机制。仿真实验结果表明:QPSO算法在优化性能上优于传统遗传算法(GA)和量子遗传算法(QGA),能够有效提高网络整体的感知能力,该方法用于传感器节点优化部署是可行的。
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| 关 键 词： | 无线传感器网络 节点 优化 部署 量子粒子群 |
Optimization of wireless sensor networks nodes based on quantum particle swarm optimal algorithm |
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| WANG Yan-ping,ZHANG Hui-min,LIU Xin-gui. Optimization of wireless sensor networks nodes based on quantum particle swarm optimal algorithm[J]. Transducer and Microsystem Technology, 2010, 29(2) |
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| Authors: | WANG Yan-ping ZHANG Hui-min LIU Xin-gui |
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| Affiliation: | WANG Yan-ping1,ZHANG Hui-min1,LIU Xin-gui2(1.Department of Information Engineering,Zhengzhou Railway Vocational&Technical College,Zhengzhou 450052,China,2.Institute of Surveying , Mapping,PLA Information Engineering University,China) |
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| Abstract: | The distribution optimization problems of node-aware of wireless sensor networks are studied.A distributed optimization mechanism is presented based on quantum particle swarm optimization(QPSO)algorithm.Simulation results show that QPSO algorithm is superior to the traditional genetic algorithm(GA)and quantum genetic algorithm(QGA),can effectively improve network capacity of the overall perception.The method used to optimize the deployment of sensor nodes is feasible. |
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| Keywords: | wireless sensor networks(WSNs) node optimization deployment quantum particle swarm optimization(QPSO) |
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