Coverage optimization algorithm based on VF-CS in mobile sensor network

Guanghui LI; Shihong HU

doi:10.11959/j.issn.1000-436x.2018039

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Coverage optimization algorithm based on VF-CS in mobile sensor network

Special Issue on Internet of Things and Its Security | 更新时间：2024-06-05

- Coverage optimization algorithm based on VF-CS in mobile sensor network
- Journal on Communications Vol. 39, Issue 3, Pages: 95-107(2018)
- 作者机构：
  
  1. 江南大学物联网工程学院，江苏无锡 214122
  2. 江苏省无线传感网高技术研究重点实验室，江苏南京 210003
  3. 物联网技术应用教育部工程技术研究中心，江苏无锡 214122
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(61472368);The National Natural Science Foundation of China(61174023);The Key Project of the Jiangsu Provincial Research and Development(BE2016627);The Fundamental Research Funds for the Central Universities(RP51635B);International Scientific and Technological Cooperation Projects of Wuxi(CZE02H1706)
- DOI：10.11959/j.issn.1000-436x.2018039
  CLC： TP393
- Online First：2018-03，
  
  Published：25 March 2018
- 稿件说明：
移动端阅览
Guanghui LI, Shihong HU. Coverage optimization algorithm based on VF-CS in mobile sensor network[J]. Journal on Communications, 2018, 39(3): 95-107.
DOI：

Guanghui LI, Shihong HU. Coverage optimization algorithm based on VF-CS in mobile sensor network[J]. Journal on Communications, 2018, 39(3): 95-107. DOI： 10.11959/j.issn.1000-436x.2018039.

摘要

在野外环境部署大规模传感器网络时，往往采用随机部署方式，导致覆盖率不高。为此提出一种基于虚拟力（virtual force）扰动和布谷鸟搜索（CS

Cuckoo search）的移动传感器网络覆盖优化算法（VF-CS）。首先，对传感器节点进行Voronoi图划分，形成独立的泰森多边形（Thiessen polygon）。其次，对泰森多边形内的节点进行虚拟力的分析，将多边形顶点和邻居节点的作用力作为布谷鸟搜索位置更新的扰动因子。最后，通过布谷鸟搜索引导节点移动实现覆盖优化。仿真实验结果表明，与以往基于Voronoi图的覆盖优化算法相比，VF-CS算法提高了覆盖率，减少了节点平均移动距离。

Abstract

A random placement of large-scale sensor network in the outdoor environment often causes low coverage.An area coverage optimization algorithm of mobile sensor network (MSN) based on virtual force perturbation and Cuckoo search (VF-CS) was proposed.Firstly

the virtual force of the sensor nodes within the Thiessen polygon was analyzed based on the partitioning of Voronoi diagram of the monitoring area.Secondly

the force of polygon vertices and neighbor nodes was taken as the perturbation factor for updating the node’s location of the Cuckoo search (CS).Finally

the VF-CS guided the node to move so as to achieve the optimal coverage.The simulation results demonstrate that the proposed algorithm has higher coverage and shorter average moving distance of nodes than the Voronoi diagram based algorithms in literatures.

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references

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