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Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks

Location information is a required concern for localization-based service application in the field of wireless sensor networks (WSNs). Distance Vector-Hop (DV-Hop) algorithm as the most typical range-free localization scheme is more suitable for large-scaled WSNs. Its localization performance is goo...

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Main Authors: Han, Fengrong, Izzeldin, Ibrahim Mohamed Abdelaziz, Kamarul Hawari, Ghazali, Zhao, Yue, Li, Ning
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2023
Subjects:
T Technology (General)
TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/38265/1/Optimized%20range-free%20localization%20scheme%20using%20autonomous%20groups%20particles%20swarm%20optimization.pdf
http://umpir.ump.edu.my/id/eprint/38265/
https://doi.org/10.1109/ACCESS.2023.3257567
https://doi.org/10.1109/ACCESS.2023.3257567
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spelling my.ump.umpir.382652023-10-02T07:48:05Z http://umpir.ump.edu.my/id/eprint/38265/ Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks Han, Fengrong Izzeldin, Ibrahim Mohamed Abdelaziz Kamarul Hawari, Ghazali Zhao, Yue Li, Ning T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Location information is a required concern for localization-based service application in the field of wireless sensor networks (WSNs). Distance Vector-Hop (DV-Hop) algorithm as the most typical range-free localization scheme is more suitable for large-scaled WSNs. Its localization performance is good in even distributed networks. However, it demonstrated extremely poor accuracy under anisotropic networks, which is an urgent problem that need to be addressed. Accordingly, an optimized DV-Hop localization algorithm is put forward in this study with considering several anisotropic factors. Accumulated hop size error and collinearity are two main reasons that led to low accuracy and poor stability. Hence, hop size error of anchors is reduced by introducing distance gap based on anchors. Besides, weighted least square method is adopted to replace the least square method to against anisotropic factors caused by irregular radio patterns. Moreover, an Autonomous Groups Particles Swarm Optimization (AGPSO) is employed to further optimize the obtained coordinate in the first round. It developed a novel method to determine localization coverage. The localization coverage is also added to be one evaluation metric in our study, which makes up for the lack of this evaluation indicator in most of the studies. Simulation results display good localization accuracy and strong stability under anisotropic networks. In addition, it also concluded that metaheuristic optimization algorithm and weighted least square method are more suitable to conquer anisotropic factor. It briefly points out a new direction for the future research work in the localization area under anisotropic networks. Institute of Electrical and Electronics Engineers Inc. 2023 Article PeerReviewed pdf en cc_by_nc_nd_4 http://umpir.ump.edu.my/id/eprint/38265/1/Optimized%20range-free%20localization%20scheme%20using%20autonomous%20groups%20particles%20swarm%20optimization.pdf Han, Fengrong and Izzeldin, Ibrahim Mohamed Abdelaziz and Kamarul Hawari, Ghazali and Zhao, Yue and Li, Ning and UNSPECIFIED (2023) Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks. IEEE Access, 11. pp. 26906-26920. ISSN 2169-3536. (Published) https://doi.org/10.1109/ACCESS.2023.3257567 https://doi.org/10.1109/ACCESS.2023.3257567
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic T Technology (General)
TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
spellingShingle T Technology (General)
TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
Han, Fengrong
Izzeldin, Ibrahim Mohamed Abdelaziz
Kamarul Hawari, Ghazali
Zhao, Yue
Li, Ning
Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks
description Location information is a required concern for localization-based service application in the field of wireless sensor networks (WSNs). Distance Vector-Hop (DV-Hop) algorithm as the most typical range-free localization scheme is more suitable for large-scaled WSNs. Its localization performance is good in even distributed networks. However, it demonstrated extremely poor accuracy under anisotropic networks, which is an urgent problem that need to be addressed. Accordingly, an optimized DV-Hop localization algorithm is put forward in this study with considering several anisotropic factors. Accumulated hop size error and collinearity are two main reasons that led to low accuracy and poor stability. Hence, hop size error of anchors is reduced by introducing distance gap based on anchors. Besides, weighted least square method is adopted to replace the least square method to against anisotropic factors caused by irregular radio patterns. Moreover, an Autonomous Groups Particles Swarm Optimization (AGPSO) is employed to further optimize the obtained coordinate in the first round. It developed a novel method to determine localization coverage. The localization coverage is also added to be one evaluation metric in our study, which makes up for the lack of this evaluation indicator in most of the studies. Simulation results display good localization accuracy and strong stability under anisotropic networks. In addition, it also concluded that metaheuristic optimization algorithm and weighted least square method are more suitable to conquer anisotropic factor. It briefly points out a new direction for the future research work in the localization area under anisotropic networks.
format Article
author Han, Fengrong
Izzeldin, Ibrahim Mohamed Abdelaziz
Kamarul Hawari, Ghazali
Zhao, Yue
Li, Ning
author_facet Han, Fengrong
Izzeldin, Ibrahim Mohamed Abdelaziz
Kamarul Hawari, Ghazali
Zhao, Yue
Li, Ning
author_sort Han, Fengrong
title Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks
title_short Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks
title_full Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks
title_fullStr Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks
title_full_unstemmed Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks
title_sort optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2023
url http://umpir.ump.edu.my/id/eprint/38265/1/Optimized%20range-free%20localization%20scheme%20using%20autonomous%20groups%20particles%20swarm%20optimization.pdf
http://umpir.ump.edu.my/id/eprint/38265/
https://doi.org/10.1109/ACCESS.2023.3257567
https://doi.org/10.1109/ACCESS.2023.3257567
_version_ 1822923618968928256
score 13.232406

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