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Energy-Balanced Multisensory Scheduling for Target Tracking in Wireless Sensor Networks.

Juan Feng1, Hongwei Zhao2

  • 1School of Aerospace Science and Technology, Xidian University, Xi'an 710071, China. fengj@xidian.edu.cn.

Sensors (Basel, Switzerland)
|October 27, 2018
PubMed
Summary

This study introduces an energy-balanced multisensory scheduling strategy (EBMS) for wireless sensor networks (WSNs). EBMS enhances network lifetime by optimizing sleep schedules for both communication and sensing modules in multi-sensor nodes.

Keywords:
WSNsenergy balancemultisensory schedulingtarget tracking

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Network Engineering

Background:

  • Wireless Sensor Networks (WSNs) require efficient energy management to extend operational lifetime.
  • Existing scheduling strategies often overlook the distinct energy demands of multiple sensor modules within a single node.
  • High-energy consuming modules, like video sensors, significantly impact energy efficiency in multisensory networks.

Purpose of the Study:

  • To propose a distributed and energy-balanced multisensory scheduling strategy (EBMS) for target tracking WSNs.
  • To address the energy efficiency challenges posed by multisensory nodes with varying module power requirements.
  • To optimize sleep scheduling for both communication and sensing modules within each node.

Main Methods:

  • Organizing the WSN into clustering structures with adaptive sleep time assignments by cluster heads based on member positions.
  • Implementing an energy-balanced parameter to equalize energy consumption across all network nodes.
  • Utilizing a multi-hop coordination scheme for inter-cluster cooperation to maximize energy conservation.

Main Results:

  • The proposed EBMS strategy effectively manages sleep schedules for both communication and sensing modules.
  • EBMS demonstrates superior energy efficiency compared to existing state-of-the-art approaches in multisensory WSNs.
  • The energy-balanced parameter successfully equalizes energy consumption among nodes, prolonging network life.

Conclusions:

  • EBMS provides an effective solution for energy management in multisensory WSNs, particularly for target tracking applications.
  • The strategy's distributed nature and focus on individual module scheduling enhance overall network longevity.
  • EBMS represents a significant advancement in optimizing energy efficiency for complex WSN deployments.