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On-Demand Charging Management Model and Its Optimization for Wireless Renewable Sensor Networks.

Sandrine Mukase1, Kewen Xia1, Abubakar Umar2,3

  • 1School of Electronics and Information Engineering, Hebei University of Technology, Tianjin 300401, China.

Sensors (Basel, Switzerland)
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Wireless energy transfer (WET) resolves wireless sensor network (WSN) energy issues. A new particle swarm optimization scheme efficiently manages charging, reducing energy consumption and travel distance for longer network operation.

Keywords:
energy consumptionenergy renewable management systemparticle swarm optimizationwireless energy transferwireless renewable sensor networks

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Area of Science:

  • Wireless communication and networking
  • Energy systems and management
  • Optimization algorithms

Background:

  • Wireless sensor networks (WSNs) face significant energy and lifespan challenges.
  • Traditional charging schemes for WSNs can be inefficient, leading to high energy consumption and travel distances for charging devices.
  • Effective energy management is crucial for the sustained operation of WSNs.

Purpose of the Study:

  • To investigate wireless energy transfer (WET) for resolving energy and lifespan issues in wireless sensor networks (WSNs).
  • To develop an efficient periodic charging scheme using a wireless mobile charging device (WMCD).
  • To reduce overall system energy consumption, minimize the total distance traveled by the WMCD, and increase its vacation time.

Main Methods:

  • Proposed an energy renewable management system based on particle swarm optimization (ERMS-PSO).
  • Introduced minimum energy level (emin) and threshold energy level (ethresh) to manage sensor node charging.
  • Implemented a strategy where the WMCD visits only nodes falling below ethresh, rather than all nodes, in each charging cycle.

Main Results:

  • The proposed ERMS-PSO strategy significantly reduces total energy consumption and the distance traveled by the WMCD.
  • The strategy effectively increases the vacation time ratio of the charging device.
  • Mathematical outcomes demonstrate considerable improvements in network performance and operational longevity.

Conclusions:

  • The ERMS-PSO strategy offers a practical and efficient solution for managing energy in WSNs.
  • This approach enhances network sustainability by optimizing charging cycles and reducing resource expenditure.
  • The proposed method is more practical for real-world networks due to its reduced complexity and improved operational efficiency.