An Optimized Strategy Coverage Control Algorithm for WSN

The problem of using lesser wireless sensor network nodes to achieve coverage and connection of certain areas under given coverage conditions is a priority and hotspot issue of WSN. For this reason, in this paper, an optimized strategy coverage control (OSCC) algorithm is proposed. First of all, a r...

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Main Authors: Zeyu Sun, Weiguo Wu, Huanzhao Wang, Heng Chen, Wei Wei
Format: Article
Language:English
Published: SAGE Publishing 2014-07-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1155/2014/976307
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spelling doaj-65401dc23fbe4093ac01ecd7fc4497312020-11-25T04:01:00ZengSAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772014-07-011010.1155/2014/976307976307An Optimized Strategy Coverage Control Algorithm for WSNZeyu Sun0Weiguo Wu1Huanzhao Wang2Heng Chen3Wei Wei4 Computer and Information Engineering Department, Luoyang Institute of Technology, Luoyang, Henan 471023, China School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an, Shanxi 710049, China School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an, Shanxi 710049, China School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an, Shanxi 710049, China School of Computer Science and Engineering, Xi'an University of Technology, Xi'an, Shanxi 710048, ChinaThe problem of using lesser wireless sensor network nodes to achieve coverage and connection of certain areas under given coverage conditions is a priority and hotspot issue of WSN. For this reason, in this paper, an optimized strategy coverage control (OSCC) algorithm is proposed. First of all, a relation mapping model of sensor nodes and target nodes is established by OSCC which is based on geometric figure and related theories, probability theory, converge property, and so forth to complete effective reasoning and calculate certain network models. Secondly, OSCC makes efficient analysis of the calculating results figure out the least number of sensor nodes to cover specific monitoring area. Thirdly, OSCC picks out the optimal routing solution while conducting combinatorial optimization of routing path using ant colony optimization (ACO) algorithm, thus reducing the energy spending of whole network. In the end, this paper verifies OSCC algorithm by simulation experiment and proves it can use least sensor nodes to effectively cover target area. Also, OSCC helps greatly reduce network energy consuming, minimize network resources layout costs, and enhance network life cycle, simultaneously.https://doi.org/10.1155/2014/976307
collection DOAJ
language English
format Article
sources DOAJ
author Zeyu Sun
Weiguo Wu
Huanzhao Wang
Heng Chen
Wei Wei
spellingShingle Zeyu Sun
Weiguo Wu
Huanzhao Wang
Heng Chen
Wei Wei
An Optimized Strategy Coverage Control Algorithm for WSN
International Journal of Distributed Sensor Networks
author_facet Zeyu Sun
Weiguo Wu
Huanzhao Wang
Heng Chen
Wei Wei
author_sort Zeyu Sun
title An Optimized Strategy Coverage Control Algorithm for WSN
title_short An Optimized Strategy Coverage Control Algorithm for WSN
title_full An Optimized Strategy Coverage Control Algorithm for WSN
title_fullStr An Optimized Strategy Coverage Control Algorithm for WSN
title_full_unstemmed An Optimized Strategy Coverage Control Algorithm for WSN
title_sort optimized strategy coverage control algorithm for wsn
publisher SAGE Publishing
series International Journal of Distributed Sensor Networks
issn 1550-1477
publishDate 2014-07-01
description The problem of using lesser wireless sensor network nodes to achieve coverage and connection of certain areas under given coverage conditions is a priority and hotspot issue of WSN. For this reason, in this paper, an optimized strategy coverage control (OSCC) algorithm is proposed. First of all, a relation mapping model of sensor nodes and target nodes is established by OSCC which is based on geometric figure and related theories, probability theory, converge property, and so forth to complete effective reasoning and calculate certain network models. Secondly, OSCC makes efficient analysis of the calculating results figure out the least number of sensor nodes to cover specific monitoring area. Thirdly, OSCC picks out the optimal routing solution while conducting combinatorial optimization of routing path using ant colony optimization (ACO) algorithm, thus reducing the energy spending of whole network. In the end, this paper verifies OSCC algorithm by simulation experiment and proves it can use least sensor nodes to effectively cover target area. Also, OSCC helps greatly reduce network energy consuming, minimize network resources layout costs, and enhance network life cycle, simultaneously.
url https://doi.org/10.1155/2014/976307
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