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An improved DV-Hop algorithm based on PSO and Modified DE algorithm

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Abstract

Wireless sensor networks (WSN) have been used in many fields, and the localization technology is one of the core technologies of WSN. Distance Vector-Hop (DV-Hop) algorithm is one of the localization algorithms for WSN, which is widely used because of its simple principle and low cost. The traditional DV-Hop algorithm has high localization error, so the PMDDV-Hop algorithm is proposed in this paper. First, the average hop-size of anchor nodes is optimized by the Particle Swarm Optimization (PSO) algorithm to reduce the accumulation of errors. Then the coordinates of the unknown nodes are optimized using the Differential Evolutionary (DE) algorithm. To reduce the probability of falling into local optimum during evolution, the levy flight strategy is introduced into the DE algorithm to increase the diversity of the population. To further improve the performance of the PMDDV-Hop algorithm, the mutation factor and crossover factor in the DE algorithm are dynamically changed to make them adaptive to the degree of population evolution. Finally, extensive experimental simulations are conducted to evaluate the effectiveness of the PMDDV-Hop algorithm. Experimental results show that the PMDDV-Hop algorithm can effectively reduce the localization error.

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  1. Computer Science and Engineering, Shandong University of Science and Technology, Xin’an Street, Qingdao, 266590, Shandong, China

    Haibin Sun, Dong Wang, Hongxing Li & Ziran Meng

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  1. Haibin Sun
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Contributions

All authors contributed to the study conception and design. The first draft of the manuscript was written by Haibin Sun and Dong Wang and all authors commented on previous versions of the manuscript. Material preparation, data analysis were performed by Ziran Meng and Hongxing Li. All authors read and approved the final manuscript.

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Correspondence to Dong Wang.

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Sun, H., Wang, D., Li, H. et al. An improved DV-Hop algorithm based on PSO and Modified DE algorithm. Telecommun Syst 82, 403–418 (2023). https://doi.org/10.1007/s11235-023-00991-w

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