Node Localization Algorithm Based on Modified Archimedes Optimization Algorithm in Wireless Sensor Networks
Node localization information plays an important role in wireless sensor networks (WSNs). To solve the problem of low localization accuracy of distance vector hop (DV-Hop) localization algorithm in wireless sensor networks, an improved localization algorithm called MAOADV-Hop based on the modified A...
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| Vydáno v: | Journal of sensors Ročník 2022; s. 1 - 18 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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New York
Hindawi
07.06.2022
John Wiley & Sons, Inc |
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| ISSN: | 1687-725X, 1687-7268 |
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| Abstract | Node localization information plays an important role in wireless sensor networks (WSNs). To solve the problem of low localization accuracy of distance vector hop (DV-Hop) localization algorithm in wireless sensor networks, an improved localization algorithm called MAOADV-Hop based on the modified Archimedes optimization algorithm (MAOA) and DV-Hop is proposed, which can achieve the balance between the localization speed and the localization precision. Firstly, tent chaotic mapping and particle swarm optimization (PSO) algorithm are introduced into Archimedes optimization algorithm to improve the initial population diversity and change the update rules of density and volume, which improve the global convergence ability and convergence speed of the algorithm. Secondly, the MAOA is used to replace the least square part of the DV-Hop localization algorithm to improve the localization accuracy of the algorithm. Finally, MAOADV-Hop is verified through four different network environments and compared with DE_DV-Hop, BOA_DV-Hop, and DV-Hop. The simulation results show that the localization speed of the proposed approach is faster than that of DE_DV-Hop and BOA_DV-Hop, and the localization error is less than that of DV-Hop, DE_DV-Hop, and BOA_DV-Hop. |
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| AbstractList | Node localization information plays an important role in wireless sensor networks (WSNs). To solve the problem of low localization accuracy of distance vector hop (DV-Hop) localization algorithm in wireless sensor networks, an improved localization algorithm called MAOADV-Hop based on the modified Archimedes optimization algorithm (MAOA) and DV-Hop is proposed, which can achieve the balance between the localization speed and the localization precision. Firstly, tent chaotic mapping and particle swarm optimization (PSO) algorithm are introduced into Archimedes optimization algorithm to improve the initial population diversity and change the update rules of density and volume, which improve the global convergence ability and convergence speed of the algorithm. Secondly, the MAOA is used to replace the least square part of the DV-Hop localization algorithm to improve the localization accuracy of the algorithm. Finally, MAOADV-Hop is verified through four different network environments and compared with DE_DV-Hop, BOA_DV-Hop, and DV-Hop. The simulation results show that the localization speed of the proposed approach is faster than that of DE_DV-Hop and BOA_DV-Hop, and the localization error is less than that of DV-Hop, DE_DV-Hop, and BOA_DV-Hop. |
| Author | Yang, Jing Qin, Tao Cheng, Mangmang |
| Author_xml | – sequence: 1 givenname: Mangmang orcidid: 0000-0003-1116-277X surname: Cheng fullname: Cheng, Mangmang organization: Electrical Engineering CollegeGuizhou UniversityGuiyang 550025Chinagzu.edu.cn – sequence: 2 givenname: Tao surname: Qin fullname: Qin, Tao organization: Electrical Engineering CollegeGuizhou UniversityGuiyang 550025Chinagzu.edu.cn – sequence: 3 givenname: Jing orcidid: 0000-0002-6407-1276 surname: Yang fullname: Yang, Jing organization: Electrical Engineering CollegeGuizhou UniversityGuiyang 550025Chinagzu.edu.cn |
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| ContentType | Journal Article |
| Copyright | Copyright © 2022 Mangmang Cheng et al. Copyright © 2022 Mangmang Cheng et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0 |
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| SubjectTerms | Accuracy Algorithms Convergence Localization Optimization algorithms Particle swarm optimization Population Sensors Wireless networks Wireless sensor networks |
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| Title | Node Localization Algorithm Based on Modified Archimedes Optimization Algorithm in Wireless Sensor Networks |
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