Node Localization in Wireless Sensor Network by Ant Lion Optimization
Node location is a critical demand in some popularity of Wireless sensor network (WSN) applications. This paper proposes a node location identification in WSN based on a combined Ant Lion Optimizer (ALO) with a typical model of localization. The fitness function is modeled mathematically based on es...
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2022
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| Truy cập trực tuyến: | https://lib.hpu.edu.vn/handle/123456789/34478 |
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oai:https:--lib.hpu.edu.vn:123456789-344782024-10-04T08:27:40Z Node Localization in Wireless Sensor Network by Ant Lion Optimization Đào, Thị Kiên Pan, Jeng Shyang Nguyễn, Trọng Thể Chu, Shu Chuan Trần, Hữu Trung Nguyễn, Trịnh Đông Vũ, Ngọc Thanh Ant Lion Optimizer Localization Wireless Sensor Network Positioning accuracy Node location is a critical demand in some popularity of Wireless sensor network (WSN) applications. This paper proposes a node location identification in WSN based on a combined Ant Lion Optimizer (ALO) with a typical model of localization. The fitness function is modeled mathematically based on estimating distances of the WSN nodes. The updating solutions of the population are figured out for position correcting to improve the node positioning accuracy. The effects of parameters like node density and communicating range is verified in the experiments to evaluate the performance of the proposed method in terms of concerning average localization error and success ratio. Compared to the results of the test with Cuckoo Search (CS) and Particle swarm optimization (PSO) shows that the proposed approach effectively offers a better competitor in finding location accuracy. 2022-04-13T02:18:39Z 2022-04-13T02:18:39Z 2021 Article https://lib.hpu.edu.vn/handle/123456789/34478 en 11 tr. application/pdf application/pdf Springer |
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Trường Đại học Quản lý và Công nghệ Hải Phòng |
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DSpaceHPU |
| language |
English |
| topic |
Ant Lion Optimizer Localization Wireless Sensor Network Positioning accuracy |
| spellingShingle |
Ant Lion Optimizer Localization Wireless Sensor Network Positioning accuracy Đào, Thị Kiên Pan, Jeng Shyang Nguyễn, Trọng Thể Chu, Shu Chuan Trần, Hữu Trung Nguyễn, Trịnh Đông Vũ, Ngọc Thanh Node Localization in Wireless Sensor Network by Ant Lion Optimization |
| description |
Node location is a critical demand in some popularity of Wireless sensor network (WSN) applications. This paper proposes a node location identification in WSN based on a combined Ant Lion Optimizer (ALO) with a typical model of localization. The fitness function is modeled mathematically based on estimating distances of the WSN nodes. The updating solutions of the population are figured out for position correcting to improve the node positioning accuracy. The effects of parameters like node density and communicating range is verified in the experiments to evaluate the performance of the proposed method in terms of concerning average localization error and success ratio. Compared to the results of the test with Cuckoo Search (CS) and Particle swarm optimization (PSO) shows that the proposed approach effectively offers a better competitor in finding location accuracy. |
| format |
Article |
| author |
Đào, Thị Kiên Pan, Jeng Shyang Nguyễn, Trọng Thể Chu, Shu Chuan Trần, Hữu Trung Nguyễn, Trịnh Đông Vũ, Ngọc Thanh |
| author_facet |
Đào, Thị Kiên Pan, Jeng Shyang Nguyễn, Trọng Thể Chu, Shu Chuan Trần, Hữu Trung Nguyễn, Trịnh Đông Vũ, Ngọc Thanh |
| author_sort |
Đào, Thị Kiên |
| title |
Node Localization in Wireless Sensor Network by Ant Lion Optimization |
| title_short |
Node Localization in Wireless Sensor Network by Ant Lion Optimization |
| title_full |
Node Localization in Wireless Sensor Network by Ant Lion Optimization |
| title_fullStr |
Node Localization in Wireless Sensor Network by Ant Lion Optimization |
| title_full_unstemmed |
Node Localization in Wireless Sensor Network by Ant Lion Optimization |
| title_sort |
node localization in wireless sensor network by ant lion optimization |
| publisher |
Springer |
| publishDate |
2022 |
| url |
https://lib.hpu.edu.vn/handle/123456789/34478 |
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