A Mechanism Filling Sensing Holes for Detecting the Boundary of Continuous Objects in Hybrid Sparse Wireless Sensor Networks

Nowadays, the rapidly developed Internet of Things requires the ability handling information efficiently to deal with the intelligent applications. Wireless sensor networks (WSNs), which act as an important interface between physical environment and Internet of Things, have been applied in numerous...

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Main Authors: Jianming Xiang, Zhangbing Zhou, Lei Shu, Taj Rahman, Qun Wang
Format: Article
Language:English
Published: IEEE 2017-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/7827153/
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author Jianming Xiang
Zhangbing Zhou
Lei Shu
Taj Rahman
Qun Wang
author_facet Jianming Xiang
Zhangbing Zhou
Lei Shu
Taj Rahman
Qun Wang
author_sort Jianming Xiang
collection DOAJ
description Nowadays, the rapidly developed Internet of Things requires the ability handling information efficiently to deal with the intelligent applications. Wireless sensor networks (WSNs), which act as an important interface between physical environment and Internet of Things, have been applied in numerous applications. As a kind of important application of WSNs, the continuous objects boundary detection is popular in industry. However, the long-term maintenance for the traditional WSNs, which are used to monitor the leakage of continuous objects, is expensive. Thus, we use sparse WSNs to address this issue. But, the inaccuracy of the sparse network is a big problem while the information of continuous objects is used to arrange retreat path for people. To access this problem, we propose our mechanism, which used hybrid network to compromise the accuracy and cost of maintenance. The sensing holes will be detected by using Voronoi diagram, before the network starts to work. After the static sensor nodes get the value of the toxic air, the mechanism can calculate the high variation location, which give weights to the sensing holes, in the static sensor networks. Thus, the sensing holes, which selected by both spatial and data variation factors will be list in a target nodes list for the mobile sensor node. Finally, the optimal path considering both distance and priority for the mobile sensor will be plan out. Experimental evaluation shows that there is an optimal amount of the static nodes decided by the sensing radius and the size of area. And it reduces the energy consumption by the static networks.
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spelling doaj.art-419f5e83961f45fbbd756404c16c0d2b2022-12-21T20:18:49ZengIEEEIEEE Access2169-35362017-01-0157922793510.1109/ACCESS.2017.26544787827153A Mechanism Filling Sensing Holes for Detecting the Boundary of Continuous Objects in Hybrid Sparse Wireless Sensor NetworksJianming Xiang0https://orcid.org/0000-0002-5512-7119Zhangbing Zhou1Lei Shu2Taj Rahman3https://orcid.org/0000-0001-9590-3744Qun Wang4School of Information Engineering, China University of Geosciences, Beijing, ChinaSchool of Information Engineering, China University of Geosciences, Beijing, ChinaGuangdong University of Petrochemical TechnologySchool of Information Engineering, University of Science and Technology Beijing, Beijing, ChinaSchool of Information Engineering, China University of Geosciences, Beijing, ChinaNowadays, the rapidly developed Internet of Things requires the ability handling information efficiently to deal with the intelligent applications. Wireless sensor networks (WSNs), which act as an important interface between physical environment and Internet of Things, have been applied in numerous applications. As a kind of important application of WSNs, the continuous objects boundary detection is popular in industry. However, the long-term maintenance for the traditional WSNs, which are used to monitor the leakage of continuous objects, is expensive. Thus, we use sparse WSNs to address this issue. But, the inaccuracy of the sparse network is a big problem while the information of continuous objects is used to arrange retreat path for people. To access this problem, we propose our mechanism, which used hybrid network to compromise the accuracy and cost of maintenance. The sensing holes will be detected by using Voronoi diagram, before the network starts to work. After the static sensor nodes get the value of the toxic air, the mechanism can calculate the high variation location, which give weights to the sensing holes, in the static sensor networks. Thus, the sensing holes, which selected by both spatial and data variation factors will be list in a target nodes list for the mobile sensor node. Finally, the optimal path considering both distance and priority for the mobile sensor will be plan out. Experimental evaluation shows that there is an optimal amount of the static nodes decided by the sensing radius and the size of area. And it reduces the energy consumption by the static networks.https://ieeexplore.ieee.org/document/7827153/Static wireless sensor networksmobile sensorVoronoi diagramoptimum path
spellingShingle Jianming Xiang
Zhangbing Zhou
Lei Shu
Taj Rahman
Qun Wang
A Mechanism Filling Sensing Holes for Detecting the Boundary of Continuous Objects in Hybrid Sparse Wireless Sensor Networks
IEEE Access
Static wireless sensor networks
mobile sensor
Voronoi diagram
optimum path
title A Mechanism Filling Sensing Holes for Detecting the Boundary of Continuous Objects in Hybrid Sparse Wireless Sensor Networks
title_full A Mechanism Filling Sensing Holes for Detecting the Boundary of Continuous Objects in Hybrid Sparse Wireless Sensor Networks
title_fullStr A Mechanism Filling Sensing Holes for Detecting the Boundary of Continuous Objects in Hybrid Sparse Wireless Sensor Networks
title_full_unstemmed A Mechanism Filling Sensing Holes for Detecting the Boundary of Continuous Objects in Hybrid Sparse Wireless Sensor Networks
title_short A Mechanism Filling Sensing Holes for Detecting the Boundary of Continuous Objects in Hybrid Sparse Wireless Sensor Networks
title_sort mechanism filling sensing holes for detecting the boundary of continuous objects in hybrid sparse wireless sensor networks
topic Static wireless sensor networks
mobile sensor
Voronoi diagram
optimum path
url https://ieeexplore.ieee.org/document/7827153/
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