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An IMOA DV-Hop localization algorithm in WSN based on hop count and hop distance correction

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Abstract

Wireless sensor networks (WSNs) have been widely used in environmental monitoring due to their low cost advantages. In WSNs monitoring, the location information is significant, because data collected by sensor nodes is valuable only if the locations of nodes are known. DV-Hop algorithm is a popular localization algorithm in WSNs monitoring. However, DV-hop has low localization accuracy due to its imperfect hop count, hop distance and location calculation mechanism. Therefore, in order to improve its localization accuracy, we improve the three stages of DV-hop respectively: Firstly, the anchor node broadcasts in three types of communication radius to reduce hop count error. Secondly, we utilize local average hop distance to reduce the hop distance calculation error. Finally, we use the heuristic algorithm MOA to calculate node positions. Meanwhile, we utilize the good point set, t-distribution and Levy flight to improve the global optimization ability of MOA. In simulation experiments, we use Matlab2018a to verify algorithm performance. The simulation results show that the proposed algorithm outperforms the comparison algorithm in different communication radius, number of anchor nodes, and total number of nodes. It performs optimally in both localization efficiency and accuracy, and has better robustness.

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The data that supporting the findings of this study are available from the corresponding author upon reasonable request.

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Funding

This work was in part supported by Hunan Provincial Natural Science Foundation of China (2024JJ5338); National Natural Science Foundation of China (No.11875164); University of South China Postdoctoral Research star-up Fund(230XQD053).

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Xiuwu Yu and Wei Peng wrote the main part of the paper. Zixiang Zhou, Ke Zhang and Yong Liu checked the paper.

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Correspondence to Wei Peng.

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Yu, X., Peng, W., Zhou, Z. et al. An IMOA DV-Hop localization algorithm in WSN based on hop count and hop distance correction. Peer-to-Peer Netw. Appl. (2024). https://doi.org/10.1007/s12083-024-01710-1

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