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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| Format: | Article |
| Language: | English |
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Institute of Electrical and Electronics Engineers Inc.
2023
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| Online Access: | http://umpir.ump.edu.my/id/eprint/38265/1/Optimized%20range-free%20localization%20scheme%20using%20autonomous%20groups%20particles%20swarm%20optimization.pdf |
| _version_ | 1825815080061632512 |
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| 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 |
| collection | UMP |
| 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. |
| first_indexed | 2024-03-06T13:08:06Z |
| format | Article |
| id | UMPir38265 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T13:08:06Z |
| publishDate | 2023 |
| publisher | Institute of Electrical and Electronics Engineers Inc. |
| record_format | dspace |
| spelling | UMPir382652023-10-02T07:48:05Z 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 |
| 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 |
| title | 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_short | 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 |
| topic | T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/38265/1/Optimized%20range-free%20localization%20scheme%20using%20autonomous%20groups%20particles%20swarm%20optimization.pdf |
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