Optimal Multi-Base-Station Selection for Belt-Area Wireless Sensor Networks

Since underground environments, such as urban subways, tunnels, underground pipe corridors, and mine roadways, etc., are complex and changeable, the software functions of the sensor nodes in underground spaces must be updated regularly to satisfy the requirements of the monitoring center. Software u...

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Main Authors: Zhangling Duan, Xing Wei, Jianghong Han, Guoqiang Yang, Yang Lu
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8880563/
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spelling doaj-17bb5cf54d324c3ba2b141ca32746a782021-03-30T00:18:45ZengIEEEIEEE Access2169-35362019-01-01715708515710210.1109/ACCESS.2019.29491008880563Optimal Multi-Base-Station Selection for Belt-Area Wireless Sensor NetworksZhangling Duan0https://orcid.org/0000-0003-3246-8022Xing Wei1https://orcid.org/0000-0002-9667-0433Jianghong Han2https://orcid.org/0000-0003-1133-317XGuoqiang Yang3Yang Lu4School of Computer and Information, Hefei University of Technology, Hefei, ChinaSchool of Computer and Information, Hefei University of Technology, Hefei, ChinaSchool of Computer and Information, Hefei University of Technology, Hefei, ChinaSchool of Computer and Information, Hefei University of Technology, Hefei, ChinaSchool of Computer and Information, Hefei University of Technology, Hefei, ChinaSince underground environments, such as urban subways, tunnels, underground pipe corridors, and mine roadways, etc., are complex and changeable, the software functions of the sensor nodes in underground spaces must be updated regularly to satisfy the requirements of the monitoring center. Software updates cannot be traditionally conducted due to the large number of nodes, the wide distribution range and the poor underground environment; they can only be made using wireless reprogramming. Current reprogramming protocols are all designed for topologically unconstrained networks and are inefficient in routing constrained underground belt-area wireless sensor networks (BAWSNs). We propose a new reprogramming mechanism for reducing the energy and time consumption of the data downstream transmission process in BAWSNs. For network energy optimization, we identified the highest energy efficiency transmission radius. For network base-station location time optimization, an approximate (1 + &#x03B5;) algorithm that is based on gradient cyclic descent is proposed, which is of complexity O (kn<sup>2</sup>). The simulation results demonstrate that, compared with classical algorithms, the BAWSNs approximation algorithm can locate the optimal base station accurately with low time consumption.https://ieeexplore.ieee.org/document/8880563/Belt-area wireless sensor networksbase station selectionp-center problemoptimization algorithm
collection DOAJ
language English
format Article
sources DOAJ
author Zhangling Duan
Xing Wei
Jianghong Han
Guoqiang Yang
Yang Lu
spellingShingle Zhangling Duan
Xing Wei
Jianghong Han
Guoqiang Yang
Yang Lu
Optimal Multi-Base-Station Selection for Belt-Area Wireless Sensor Networks
IEEE Access
Belt-area wireless sensor networks
base station selection
p-center problem
optimization algorithm
author_facet Zhangling Duan
Xing Wei
Jianghong Han
Guoqiang Yang
Yang Lu
author_sort Zhangling Duan
title Optimal Multi-Base-Station Selection for Belt-Area Wireless Sensor Networks
title_short Optimal Multi-Base-Station Selection for Belt-Area Wireless Sensor Networks
title_full Optimal Multi-Base-Station Selection for Belt-Area Wireless Sensor Networks
title_fullStr Optimal Multi-Base-Station Selection for Belt-Area Wireless Sensor Networks
title_full_unstemmed Optimal Multi-Base-Station Selection for Belt-Area Wireless Sensor Networks
title_sort optimal multi-base-station selection for belt-area wireless sensor networks
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2019-01-01
description Since underground environments, such as urban subways, tunnels, underground pipe corridors, and mine roadways, etc., are complex and changeable, the software functions of the sensor nodes in underground spaces must be updated regularly to satisfy the requirements of the monitoring center. Software updates cannot be traditionally conducted due to the large number of nodes, the wide distribution range and the poor underground environment; they can only be made using wireless reprogramming. Current reprogramming protocols are all designed for topologically unconstrained networks and are inefficient in routing constrained underground belt-area wireless sensor networks (BAWSNs). We propose a new reprogramming mechanism for reducing the energy and time consumption of the data downstream transmission process in BAWSNs. For network energy optimization, we identified the highest energy efficiency transmission radius. For network base-station location time optimization, an approximate (1 + &#x03B5;) algorithm that is based on gradient cyclic descent is proposed, which is of complexity O (kn<sup>2</sup>). The simulation results demonstrate that, compared with classical algorithms, the BAWSNs approximation algorithm can locate the optimal base station accurately with low time consumption.
topic Belt-area wireless sensor networks
base station selection
p-center problem
optimization algorithm
url https://ieeexplore.ieee.org/document/8880563/
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AT xingwei optimalmultibasestationselectionforbeltareawirelesssensornetworks
AT jianghonghan optimalmultibasestationselectionforbeltareawirelesssensornetworks
AT guoqiangyang optimalmultibasestationselectionforbeltareawirelesssensornetworks
AT yanglu optimalmultibasestationselectionforbeltareawirelesssensornetworks
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