Cargando…

A Hybrid Optimization from Two Virtual Physical Force Algorithms for Dynamic Node Deployment in WSN Applications

With the rapid development of unmanned aerial vehicle in space exploration and national defense, large-scale wireless sensor network (WSN) became an important and effective technology. It may require highly accurate locating for the nodes in some real applications. The dynamic node topology control...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Qiang, Yi, Qiang, Tang, Rongxin, Qian, Xin, Yuan, Kai, Liu, Shiyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6928871/
https://www.ncbi.nlm.nih.gov/pubmed/31766586
http://dx.doi.org/10.3390/s19235108
_version_ 1783482572929499136
author Li, Qiang
Yi, Qiang
Tang, Rongxin
Qian, Xin
Yuan, Kai
Liu, Shiyun
author_facet Li, Qiang
Yi, Qiang
Tang, Rongxin
Qian, Xin
Yuan, Kai
Liu, Shiyun
author_sort Li, Qiang
collection PubMed
description With the rapid development of unmanned aerial vehicle in space exploration and national defense, large-scale wireless sensor network (WSN) became an important and effective technology. It may require highly accurate locating for the nodes in some real applications. The dynamic node topology control of a large-scale WSN in an unmanned region becomes a hot research topic recently, which helps improve the system connectivity and coverage. In this paper, a hybrid optimization based on two different virtual force algorithms inspired by the interactions among physical sensor nodes is proposed to address the self-consistent node deployment in a large-scale WSN. At the early stage, the deployment algorithm was to deploy the sensor nodes by leveraging the particle motions in dusty plasma to achieve the hexagonal topology of the so-called “Yukawa crystal”. After that, another virtual exchange force model was combined to present a hybrid optimization, which could yield perfect hexagonal topology, better network uniformity, higher coverage rate, and faster convergence speed. The influence of node position, velocity, and acceleration during the node deployment stage on the final network topology are carefully discussed for this scheme. It can aid engineers to control the network topology for a large number of wireless sensors with affordable system cost by choosing suitable parameters based on physical environments or application scenarios in the near future.
format Online
Article
Text
id pubmed-6928871
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-69288712019-12-26 A Hybrid Optimization from Two Virtual Physical Force Algorithms for Dynamic Node Deployment in WSN Applications Li, Qiang Yi, Qiang Tang, Rongxin Qian, Xin Yuan, Kai Liu, Shiyun Sensors (Basel) Article With the rapid development of unmanned aerial vehicle in space exploration and national defense, large-scale wireless sensor network (WSN) became an important and effective technology. It may require highly accurate locating for the nodes in some real applications. The dynamic node topology control of a large-scale WSN in an unmanned region becomes a hot research topic recently, which helps improve the system connectivity and coverage. In this paper, a hybrid optimization based on two different virtual force algorithms inspired by the interactions among physical sensor nodes is proposed to address the self-consistent node deployment in a large-scale WSN. At the early stage, the deployment algorithm was to deploy the sensor nodes by leveraging the particle motions in dusty plasma to achieve the hexagonal topology of the so-called “Yukawa crystal”. After that, another virtual exchange force model was combined to present a hybrid optimization, which could yield perfect hexagonal topology, better network uniformity, higher coverage rate, and faster convergence speed. The influence of node position, velocity, and acceleration during the node deployment stage on the final network topology are carefully discussed for this scheme. It can aid engineers to control the network topology for a large number of wireless sensors with affordable system cost by choosing suitable parameters based on physical environments or application scenarios in the near future. MDPI 2019-11-22 /pmc/articles/PMC6928871/ /pubmed/31766586 http://dx.doi.org/10.3390/s19235108 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Li, Qiang
Yi, Qiang
Tang, Rongxin
Qian, Xin
Yuan, Kai
Liu, Shiyun
A Hybrid Optimization from Two Virtual Physical Force Algorithms for Dynamic Node Deployment in WSN Applications
title A Hybrid Optimization from Two Virtual Physical Force Algorithms for Dynamic Node Deployment in WSN Applications
title_full A Hybrid Optimization from Two Virtual Physical Force Algorithms for Dynamic Node Deployment in WSN Applications
title_fullStr A Hybrid Optimization from Two Virtual Physical Force Algorithms for Dynamic Node Deployment in WSN Applications
title_full_unstemmed A Hybrid Optimization from Two Virtual Physical Force Algorithms for Dynamic Node Deployment in WSN Applications
title_short A Hybrid Optimization from Two Virtual Physical Force Algorithms for Dynamic Node Deployment in WSN Applications
title_sort hybrid optimization from two virtual physical force algorithms for dynamic node deployment in wsn applications
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6928871/
https://www.ncbi.nlm.nih.gov/pubmed/31766586
http://dx.doi.org/10.3390/s19235108
work_keys_str_mv AT liqiang ahybridoptimizationfromtwovirtualphysicalforcealgorithmsfordynamicnodedeploymentinwsnapplications
AT yiqiang ahybridoptimizationfromtwovirtualphysicalforcealgorithmsfordynamicnodedeploymentinwsnapplications
AT tangrongxin ahybridoptimizationfromtwovirtualphysicalforcealgorithmsfordynamicnodedeploymentinwsnapplications
AT qianxin ahybridoptimizationfromtwovirtualphysicalforcealgorithmsfordynamicnodedeploymentinwsnapplications
AT yuankai ahybridoptimizationfromtwovirtualphysicalforcealgorithmsfordynamicnodedeploymentinwsnapplications
AT liushiyun ahybridoptimizationfromtwovirtualphysicalforcealgorithmsfordynamicnodedeploymentinwsnapplications
AT liqiang hybridoptimizationfromtwovirtualphysicalforcealgorithmsfordynamicnodedeploymentinwsnapplications
AT yiqiang hybridoptimizationfromtwovirtualphysicalforcealgorithmsfordynamicnodedeploymentinwsnapplications
AT tangrongxin hybridoptimizationfromtwovirtualphysicalforcealgorithmsfordynamicnodedeploymentinwsnapplications
AT qianxin hybridoptimizationfromtwovirtualphysicalforcealgorithmsfordynamicnodedeploymentinwsnapplications
AT yuankai hybridoptimizationfromtwovirtualphysicalforcealgorithmsfordynamicnodedeploymentinwsnapplications
AT liushiyun hybridoptimizationfromtwovirtualphysicalforcealgorithmsfordynamicnodedeploymentinwsnapplications