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Moving target tracking through distributed clustering in directional sensor networks.

Asma Enayet1, Md Abdur Razzaque2, Mohammad Mehedi Hassan3

  • 1Green Networking Research (GNR) Group, Deptartment of Computer Science and Engineering, Facutly of Engineering and Technology, University of Dhaka, Dhaka 1000, Bangladesh. asmaenayet@gmail.com.

Sensors (Basel, Switzerland)
|December 23, 2014
PubMed
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This summary is machine-generated.

This study introduces a clustering algorithm for directional sensor networks (DSNs) to improve moving target tracking. The proposed method enhances accuracy and network lifetime by optimizing sensor activation and data collection.

Area of Science:

  • Computer Science
  • Wireless Sensor Networks
  • Target Tracking

Background:

  • Moving target tracking in directional sensor networks (DSNs) faces challenges in sensor sector optimization, precise localization, and energy-efficient data collection.
  • Current methods often activate numerous sensors, leading to high overhead, energy depletion, and decreased tracking accuracy.

Purpose of the Study:

  • To propose a novel clustering algorithm for enhanced moving target tracking in DSNs.
  • To optimize sensing and communication sectors, improve target localization accuracy, and ensure energy efficiency.

Main Methods:

  • A distributed clustering algorithm where cluster heads coordinate member nodes.
  • Optimization of active sensing and communication directions.
  • Aggregation of sensing data for precise target location determination.

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  • Dynamic activation of sleeping nodes to balance accuracy and network lifetime.

    • Main Results:

    • The proposed mechanism minimizes sensing redundancy and maximizes the number of sleeping nodes.
    • Enhanced moving target tracking accuracy and extended network lifetime were observed.
    • Simulations conducted in ns-3 demonstrated superior performance compared to existing state-of-the-art methods.

    Conclusions:

    • The developed clustering algorithm effectively addresses the challenges of moving target tracking in DSNs.
    • The dynamic node activation strategy significantly improves both tracking accuracy and network longevity.
    • The proposed approach offers a more efficient and accurate solution for DSN target tracking applications.