WSN sensor node placement approach based on multi-objective optimization

Wireless Sensor Network (WSN) with maximum coverage, minimum energy consumption and guaranteed connectivity can be achieved through an optimum sensor node placement scheme. A sensor node placement algorithm that utilizes Multi-objective Territorial Predator Scent Marking Algorithm (MOTPSMA) is prese...

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Main Authors: Abidin H.Z., Din N.M., Radzi N.A.M.
Other Authors: 52165115900
Format: Conference Paper
Published: Institute of Electrical and Electronics Engineers Inc. 2023
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spelling my.uniten.dspace-218872023-05-16T10:45:53Z WSN sensor node placement approach based on multi-objective optimization Abidin H.Z. Din N.M. Radzi N.A.M. 52165115900 9335429400 57218936786 Wireless Sensor Network (WSN) with maximum coverage, minimum energy consumption and guaranteed connectivity can be achieved through an optimum sensor node placement scheme. A sensor node placement algorithm that utilizes Multi-objective Territorial Predator Scent Marking Algorithm (MOTPSMA) is presented in this paper. The MOTPSMA deployed in this paper uses the minimum uncovered area and minimum energy consumption as the objective functions subject to full connectivity constraint. The performance of the WSN deployed with MOTPSMA is then compared with another algorithm known as Multi-objective Evolutionary Algorithm based on Fuzzy Dominance (MOEA/DFD) in terms of coverage ratio, connectivity and energy consumption. Simulation results show that the WSN deployed with the proposed sensor node placement algorithm provides a larger coverage ratio, full connectivity and lower energy consumption. © 2014 IEEE. Final 2023-05-16T02:45:53Z 2023-05-16T02:45:53Z 2014 Conference Paper 10.1109/tenconspring.2014.6863007 2-s2.0-84911951781 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84911951781&doi=10.1109%2ftenconspring.2014.6863007&partnerID=40&md5=c469a19db2061f54387f436c9d92b799 https://irepository.uniten.edu.my/handle/123456789/21887 6863007 111 115 Institute of Electrical and Electronics Engineers Inc. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Wireless Sensor Network (WSN) with maximum coverage, minimum energy consumption and guaranteed connectivity can be achieved through an optimum sensor node placement scheme. A sensor node placement algorithm that utilizes Multi-objective Territorial Predator Scent Marking Algorithm (MOTPSMA) is presented in this paper. The MOTPSMA deployed in this paper uses the minimum uncovered area and minimum energy consumption as the objective functions subject to full connectivity constraint. The performance of the WSN deployed with MOTPSMA is then compared with another algorithm known as Multi-objective Evolutionary Algorithm based on Fuzzy Dominance (MOEA/DFD) in terms of coverage ratio, connectivity and energy consumption. Simulation results show that the WSN deployed with the proposed sensor node placement algorithm provides a larger coverage ratio, full connectivity and lower energy consumption. © 2014 IEEE.
author2 52165115900
author_facet 52165115900
Abidin H.Z.
Din N.M.
Radzi N.A.M.
format Conference Paper
author Abidin H.Z.
Din N.M.
Radzi N.A.M.
spellingShingle Abidin H.Z.
Din N.M.
Radzi N.A.M.
WSN sensor node placement approach based on multi-objective optimization
author_sort Abidin H.Z.
title WSN sensor node placement approach based on multi-objective optimization
title_short WSN sensor node placement approach based on multi-objective optimization
title_full WSN sensor node placement approach based on multi-objective optimization
title_fullStr WSN sensor node placement approach based on multi-objective optimization
title_full_unstemmed WSN sensor node placement approach based on multi-objective optimization
title_sort wsn sensor node placement approach based on multi-objective optimization
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2023
_version_ 1806425855739559936
score 13.214268