Sensor Node Placement in Wireless Sensor Network Using Multi-objective Territorial Predator Scent Marking Algorithm

Optimum sensor node placement for wireless sensor network (WSN) in a monitored area is needed for cost-effective deployment. The location of sensor nodes must be able to offer maximum coverage and connectivity with minimum energy consumption. This paper proposes a sensor node placement approach that...

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Published in:Arabian Journal for Science and Engineering
Main Author: Zainol Abidin H.; Din N.M.; Yassin I.M.; Omar H.A.; Radzi N.A.M.; Sadon S.K.
Format: Article
Language:English
Published: Springer Verlag 2014
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84904861455&doi=10.1007%2fs13369-014-1292-3&partnerID=40&md5=02d57d79ba27ceaeff800f80ff9eda84
id 2-s2.0-84904861455
spelling 2-s2.0-84904861455
Zainol Abidin H.; Din N.M.; Yassin I.M.; Omar H.A.; Radzi N.A.M.; Sadon S.K.
Sensor Node Placement in Wireless Sensor Network Using Multi-objective Territorial Predator Scent Marking Algorithm
2014
Arabian Journal for Science and Engineering
39
8
10.1007/s13369-014-1292-3
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84904861455&doi=10.1007%2fs13369-014-1292-3&partnerID=40&md5=02d57d79ba27ceaeff800f80ff9eda84
Optimum sensor node placement for wireless sensor network (WSN) in a monitored area is needed for cost-effective deployment. The location of sensor nodes must be able to offer maximum coverage and connectivity with minimum energy consumption. This paper proposes a sensor node placement approach that utilizes a new biologically inspired multi-objective optimization algorithm that imitates the behaviour of a territorial predator in marking their territories with their odours known as multi-objective territorial predator scent marking algorithm (MOTPSMA). The algorithm uses the maximum coverage and minimum energy consumption objective functions with subject to full connectivity. A simulation study has been carried out to compare the performance of the proposed algorithm with the multi-objective evolutionary algorithm with fuzzy dominance-based decomposition and an integer linear programming algorithm. Simulation results show that WSN deployed using the MOTPSMA sensor node placement algorithm outperforms the performance of the other two algorithms in terms of coverage, connectivity and energy usage. © 2014 King Fahd University of Petroleum and Minerals.
Springer Verlag
2193567X
English
Article

author Zainol Abidin H.; Din N.M.; Yassin I.M.; Omar H.A.; Radzi N.A.M.; Sadon S.K.
spellingShingle Zainol Abidin H.; Din N.M.; Yassin I.M.; Omar H.A.; Radzi N.A.M.; Sadon S.K.
Sensor Node Placement in Wireless Sensor Network Using Multi-objective Territorial Predator Scent Marking Algorithm
author_facet Zainol Abidin H.; Din N.M.; Yassin I.M.; Omar H.A.; Radzi N.A.M.; Sadon S.K.
author_sort Zainol Abidin H.; Din N.M.; Yassin I.M.; Omar H.A.; Radzi N.A.M.; Sadon S.K.
title Sensor Node Placement in Wireless Sensor Network Using Multi-objective Territorial Predator Scent Marking Algorithm
title_short Sensor Node Placement in Wireless Sensor Network Using Multi-objective Territorial Predator Scent Marking Algorithm
title_full Sensor Node Placement in Wireless Sensor Network Using Multi-objective Territorial Predator Scent Marking Algorithm
title_fullStr Sensor Node Placement in Wireless Sensor Network Using Multi-objective Territorial Predator Scent Marking Algorithm
title_full_unstemmed Sensor Node Placement in Wireless Sensor Network Using Multi-objective Territorial Predator Scent Marking Algorithm
title_sort Sensor Node Placement in Wireless Sensor Network Using Multi-objective Territorial Predator Scent Marking Algorithm
publishDate 2014
container_title Arabian Journal for Science and Engineering
container_volume 39
container_issue 8
doi_str_mv 10.1007/s13369-014-1292-3
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84904861455&doi=10.1007%2fs13369-014-1292-3&partnerID=40&md5=02d57d79ba27ceaeff800f80ff9eda84
description Optimum sensor node placement for wireless sensor network (WSN) in a monitored area is needed for cost-effective deployment. The location of sensor nodes must be able to offer maximum coverage and connectivity with minimum energy consumption. This paper proposes a sensor node placement approach that utilizes a new biologically inspired multi-objective optimization algorithm that imitates the behaviour of a territorial predator in marking their territories with their odours known as multi-objective territorial predator scent marking algorithm (MOTPSMA). The algorithm uses the maximum coverage and minimum energy consumption objective functions with subject to full connectivity. A simulation study has been carried out to compare the performance of the proposed algorithm with the multi-objective evolutionary algorithm with fuzzy dominance-based decomposition and an integer linear programming algorithm. Simulation results show that WSN deployed using the MOTPSMA sensor node placement algorithm outperforms the performance of the other two algorithms in terms of coverage, connectivity and energy usage. © 2014 King Fahd University of Petroleum and Minerals.
publisher Springer Verlag
issn 2193567X
language English
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