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Three-Dimensional Localization Algorithm Based on Improved A and DV-Hop Algorithms in Wireless Sensor Network.

Xiaohu Huang1, Dezhi Han1, Mingming Cui1

  • 1Department of Information Engineering, Shanghai Maritime University, Shanghai 201306, China.

Sensors (Basel, Switzerland)
|January 13, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces the MA*-3DDV-Hop algorithm to improve 3D localization accuracy in wireless sensor networks (WSNs). The novel approach enhances node location precision and robustness compared to existing methods.

Keywords:
3DDV-HopA* algorithmInternet of Things (IoT)NSGA-IIaverage distance per hophop-count valuewireless sensor networks (WSNs)

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • Traditional wireless sensor network (WSN) localization algorithms, like DV-Hop, suffer from significant deviation and low accuracy in 3D environments.
  • The Internet of Things (IoT) relies on accurate WSN localization for effective data collection and network management.

Purpose of the Study:

  • To propose an improved wireless sensor network node location algorithm, MA*-3DDV-Hop, enhancing 3D localization accuracy.
  • To address the limitations of existing 3D localization algorithms, specifically large deviations and low precision.

Main Methods:

  • Integration of the A* algorithm with the 3DDV-Hop algorithm to create the MA*-3DDV-Hop algorithm.
  • Optimization of hop-count values and correction of average distance per hop errors.
  • Application of the NSGA-II algorithm for local coordinate optimization, utilizing selection, crossover, and mutation to achieve Pareto optimal solutions.

Main Results:

  • The MA*-3DDV-Hop algorithm demonstrates superior robustness and higher localization accuracy in diverse 3D random scenarios.
  • Achieved Pareto optimal solutions overcome premature convergence and poor convergence issues common in genetic algorithms.
  • Reduced coordinate calculation errors, leading to enhanced localization precision for WSN nodes.

Conclusions:

  • The MA*-3DDV-Hop algorithm significantly improves localization accuracy and robustness in 3D wireless sensor networks.
  • The integration of improved A* and NSGA-II offers a more effective solution compared to standard 3DDV-Hop and other variants (PSO-3DDV-Hop, GA-3DDV-Hop, N2-3DDV-Hop).
  • This enhanced algorithm is crucial for advancing IoT applications reliant on precise WSN localization.