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Enhancing Localization Efficiency and Accuracy in Wireless Sensor Networks.

Muhammad Fawad1, Muhammad Zahid Khan1, Khalil Ullah2

  • 1Department of Computer Science & Information Technology, University of Malakand, Chakdara 18800, Pakistan.

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Summary
This summary is machine-generated.

This study introduces an enhanced DV-Hop algorithm for wireless sensor networks (WSNs). The new Hop-correction and energy-efficient DV-Hop (HCEDV-Hop) method significantly improves location accuracy and reduces energy consumption.

Keywords:
DV-HopWSNaccuracyenergy efficiencylocalization

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Area of Science:

  • Wireless Sensor Networks (WSNs)
  • Localization Algorithms
  • Network Performance

Background:

  • Accurate location estimation is critical for WSN applications like tracking and surveillance.
  • Conventional DV-Hop algorithms suffer from low accuracy and high energy demands.
  • Existing enhancements to DV-Hop have limitations in static WSN environments.

Purpose of the Study:

  • To propose an enhanced DV-Hop algorithm for accurate and energy-efficient localization in static WSNs.
  • To address the accuracy and energy consumption limitations of traditional DV-Hop methods.
  • To introduce the Hop-correction and energy-efficient DV-Hop (HCEDV-Hop) algorithm.

Main Methods:

  • Correcting single-hop distances using RSSI values within a defined radius.
  • Modifying average hop distances based on actual vs. estimated distance discrepancies.
  • Employing a least-squares approach for precise unknown node location estimation.

Main Results:

  • HCEDV-Hop demonstrated significant accuracy improvements: 81.36% over basic DV-Hop, 77.99% over WCL, 39.72% over improved DV-maxHop, and 9.96% over improved DV-Hop.
  • Reduced energy consumption by 28% compared to DV-Hop and 17% compared to WCL.
  • Validated through MATLAB simulations against benchmark schemes.

Conclusions:

  • The HCEDV-Hop algorithm offers superior localization accuracy in static WSNs.
  • HCEDV-Hop effectively reduces energy consumption, enhancing WSN efficiency.
  • The proposed method provides a robust solution for location estimation challenges in WSNs.