DV-Hop Localization Algorithm for Underwater Wireless Sensor Networks based on Squirrel Algorithm Optimization

Wenkang Zhang; Yuming Mao; Huizhong Hu

doi:10.62051/ijmee.v4n3.01

Authors

Wenkang Zhang
Yuming Mao
Huizhong Hu

DOI:

https://doi.org/10.62051/ijmee.v4n3.01

Keywords:

Wireless Sensor Networks, Squirrel Algorithm, DV-Hop Localization Algorithm, Average Hop Distance

Abstract

Aiming at the problem of large errors in the positioning algorithm of underwater wireless sensor networks, an underwater DV-Hop positioning algorithm optimized based on the squirrel algorithm is proposed. The estimated position of the unknown nodes in the DV-Hop algorithm is optimized by the squirrel algorithm, and optimization is carried out with the squirrel algorithm, the number of hops between nodes is optimized using the hop count adjustment factor, the beacon nodes that will lead to a large error are removed by the use of the covariance degree, and the average hopping distance of beacon nodes is optimized using the weighted processing method, and the average value of the improved average hopping distance is taken to be the average hopping distance of each unknown node, to Improve the localization accuracy of DV-Hop algorithm. The simulation results show that the improved algorithm improves the positioning accuracy by 34.02% and 9.75% compared with the traditional 3DDV-Hop and the hopping distance optimized 3DDV-Hop, respectively.

References

[1] XU Chen, WANG Biao. A key extraction method for underwater wireless sensor networks[J]. Computer Simulation, 2023, 40(2):415-419.

[2] ZHANG Chi, ZHANG Baoheng, ZHANG Jing,et al. A review of localization techniques for underwater wireless sensor networks[J]. Computer Applications,2022,42(z1):226-235.

[3] Qiang Zhang, Qing Zhang, Lei Zhang, et al. Path planning for mobile beacons in node localization for wireless sensor networks[J]. Journal of Weapons and Equipment Engineering,2016,37(2):144-149.

[4] WAQAS KHAN M, KHAN M, Hafeez A. Localization of wireless nodes with partial connectivity in wireless sensor systems[J]. IET Wireless Sensor Systems, 2020, 10(6): 299-307.

[5] Wang Guowu. Research and improvement of DV-Hop localization algorithm for wireless sensor networks[D]. Guangxi: Guangxi Normal University,2021.

[6] WANG Lei, LIU Jingjing, QI Junyan, et al. DV-HOP positioning algorithm based on range correction and improved whale optimization[J]. Instrumentation Technology and Sensors,2022(2):116-121,126.

[7] SONG Xiaodong, SUN Lijun, CHEN Tianfei. Performance analysis and comparison of DV-Hop optimization algorithm[J]. Journal of Electronic Measurement and Instrumentation,2019,33(5):125-133.

[8] Song Yang. An iterative method for handling node flip ambiguity in node localization for wireless sensor networks [D]. Shandong: Shandong University,2014.

[9] Huei-Chao Yan, Zeng Zi-Wei, Gang Wang. An improved DV-Hop algorithm integrating hop distance correction and sparrow search[J]. Electronic Measurement Technology,2021,44(21):133-138.

[10] PAN Zhiyuan, BU Fanliang. DV-Hop positioning algorithm based on dung beetle algorithm optimization[J]. Journal of Electronic Measurement and Instrumentation,2023,37(7):33-41.

[11] Wang Guowu, Chen Yuanyan. Optimization of DV-Hop localization algorithm based on hop count correction and genetic simulated annealing[J]. Computer Science,2021,48(z1):313-316.

[12] Shi Yunong, Liu Hailong. Research on three-dimensional DV-Hop positioning algorithm based on hop count and hop distance optimization[J]. Journal of Sensing Technology,2022,35(8):1080-1085.

[13] ZHANG Jing, GUO Yi-Han. Levy flight strategy combined with 3D gray wolf optimization for DV-hop positioning algorithm[J]. Small Microcomputer Systems,2022,43(7):1518-1522.

[14] Liu Chuanzhou. Research on wireless sensor network localization algorithm based on non-ranging [D]. Jiangsu: Nanjing University of Posts and Telecommunications,2022.

[15] Nie Jinghua. Research on DV-Hop localization algorithm based on squirrel algorithm[D]. Guangxi: Guilin University of Technology,2023.