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A Hybrid Localization Algorithm for an Adaptive Strategy-Based Distance Vector-Hop and Improved Sparrow Search for

Zhiwei Sun1, Hua Wu1, Yang Liu1

  • 1School of Information Science & Electrical Engineering, Shandong Jiaotong University, Jinan 250357, China.

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|October 28, 2023
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Summary
This summary is machine-generated.

A new hybrid localization algorithm, HADSS, improves wireless sensor network accuracy. It refines hop counts and corrects distances, significantly outperforming existing methods.

Keywords:
DV-Hopimprove sparrow searchlocalization algorithmwireless sensor network

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Area of Science:

  • Computer Science
  • Electrical Engineering

Background:

  • Node localization is crucial in wireless sensor networks (WSNs).
  • The prevalent Distance Vector-Hop (DV-Hop) algorithm offers range-free localization but lacks sufficient accuracy.

Purpose of the Study:

  • To enhance the localization accuracy of WSNs.
  • To address the limitations of the standard DV-Hop algorithm.

Main Methods:

  • Proposed a hybrid localization algorithm: adaptive strategy-based Distance Vector-Hop and improved Sparrow Search (HADSS).
  • Implemented an adaptive hop count strategy with a correction factor for refined hop counts.
  • Calculated average hop distance using mean square error and corrected it using anchor node trust degree and weighting methods.

Main Results:

  • The adaptive hop count strategy reduces errors and communication overhead compared to traditional methods.
  • The combined weighting and trust degree approach minimizes average hop distance errors by utilizing both global and local network information.
  • Simulation experiments demonstrate significantly higher accuracy for HADSS compared to five existing localization algorithms.

Conclusions:

  • The HADSS algorithm offers a substantial improvement in WSN localization accuracy.
  • The proposed adaptive strategies effectively enhance the performance of DV-Hop based localization.