系统仿真学报 ›› 2017, Vol. 29 ›› Issue (1): 181-189.doi: 10.16182/j.issn1004731x.joss.201701024

• 仿真应用工程 • 上一篇    下一篇

基于PSO的有向传感器网络覆盖增强策略及仿真

张聚伟1,2, 王宇1   

  1. 1.河南科技大学,洛阳 471023;
    2.电力电子装置与系统河南省工程实验室,洛阳 471023
  • 收稿日期:2016-04-19 修回日期:2016-07-31 出版日期:2017-01-08 发布日期:2020-06-01
  • 作者简介:张聚伟(1978-),男,河南洛阳,博士,副教授,硕导,研究方向为无线传感器网络、检测技术;王宇(1991-),男,河南商丘,硕士生,研究方向为有向传感器网络。
  • 基金资助:
    国家自然科学基金(61040010,61172014,61304144),航空科学基金(20115142005)

Simulation Study of a Coverage Enhancement Scheme in Directional Sensor Network Based on Particle Swarm Algorithm

Zhang Juwei1,2, Wang Yu1   

  1. 1. Henan University of Science and Technology, Luoyang 471023, China;
    2. Power Electronics Device and System Engineering Laboratory of Henan, Luoyang 471023, China
  • Received:2016-04-19 Revised:2016-07-31 Online:2017-01-08 Published:2020-06-01

摘要: 基于有向传感器节点概率感知模型,提出了DSmT(Dezert-Smarandache theory)数据融合策略,针对有向传感器网络覆盖增强问题,提出一种基于粒子群算法的有向传感器节点部署算法,以重叠率作为适应度函数,通过迭代调整有向传感器节点的感知方向减少网络节点的重叠率,提高了网络数据可靠性。仿真结果表明,对于感知方向连续可调的有向传感器网络节点在随机部署情况下,和现有的部署方案相比,该部署算法收敛速度快,能够有效增强有向传感器网络节点利用率,提高网络覆盖率。

关键词: 有向传感器网络, 粒子群优化算法, 概率感知模型, 数据融合, 覆盖

Abstract: A Dezert-Smarandache theory (DSmT) data fusion scheme was proposed based on the probability sensing model of directional sensor. In order to enhance the coverage ratio of directional sensor network, a sensor node deployment strategy was presented based on particle swarm optimization algorithm. Overlap rate was reduced by iteratively adjusting the sensing direction, which was regarded as fitness function in the algorithm, and the reliability of data was enhanced. The simulation results show that this algorithm has a fast convergence speed for the random deployment of sensor network nodes with continuously adjustable sensing direction, can effectively enhance the utilization rate of network nodes, and improve the coverage rate of the sensor network.

Key words: directional sensor networks, particle swarm optimization, probabilistic sensing model, data fusion, coverage

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