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DR-NET: a novel mobile anchor-assisted localization method based on the density of nodes distribution

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Abstract

Considering the existing mobile anchor-assisted localization methods generally adopt a traverse strategy for the localization region, leading to an unnecessary increase in path length. The long path will cause long localization time and high energy consumption of mobile anchor. To reduce the long path of mobile anchor, this paper proposes a novel mobile anchor-assisted localization method based on the density of nodes distribution called Division of Regions Nested Equilateral Triangles path planning (DR-NET). Firstly, DR-NET divides the localization region into several small regions according to the density of nodes distribution, thereby reducing the movement in the distribution region of sensorless nodes. Secondly, the shortest path algorithm and genetic algorithm are used to calculate the shortest path of the inter-region and intra-region. Finally, the mobile anchor moves according to the planned path and assists the unknown nodes to locate. Compared with the existing classical methods LMAT, MAALRH, H-Curves and M-Curves, a series of experimental results demonstrate that DR-NET can effectively reduce the path length and energy consumption of mobile anchor by 8.56–30.66%, 4.26–28.59%, respectively. To further verify the validity and adaptability of DR-NET, we conduct experiments on localization regions with different shapes, areas, deployment strategies of nodes and structure types of nodes. The results show that DR-NET still maintains high stability in path length and localization success ratio.

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Acknowledgements

This work was supported by the National Nature Science Foundation of China (Nos. 62172435, U1804263 and 61872449), Zhongyuan Science and Technology Innovation Leading Talent Project of China (No. 214200510019).

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Authors and Affiliations

  1. Zhengzhou Institute of Information Science and Technology, Zhengzhou, 450001, Henan, China

    Guo Wei, Xiangyang Luo, Shichang Ding, Baoshan Yang & Wenyan Liu

  2. State Key Laboratory of Mathematical Engineering and Advanced Computing, Zhengzhou, 450001, Henan, China

    Guo Wei, Xiangyang Luo, Shichang Ding & Wenyan Liu

  3. Henan Province Key Laboratory of Cyberspace Situation Awareness, Zhengzhou, 450001, Henan, China

    Guo Wei, Xiangyang Luo, Shichang Ding & Wenyan Liu

Authors
  1. Guo Wei
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  2. Xiangyang Luo
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  3. Shichang Ding
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Correspondence to Xiangyang Luo.

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Wei, G., Luo, X., Ding, S. et al. DR-NET: a novel mobile anchor-assisted localization method based on the density of nodes distribution. Wireless Netw 28, 3431–3451 (2022). https://doi.org/10.1007/s11276-022-03056-z

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