Maximize Lifetime of Wireless Rechargeable Sensor Networks with Mobile Energy-Limited Charging Device

Area of Science:

• Computer Science
• Electrical Engineering
• Network Engineering

Background:

• Wireless sensor networks (WSNs) face energy limitations impacting their operational lifespan.
• Existing mobile charging device (MCD) strategies often overlook critical factors like redundant nodes, limiting network longevity.
• Improving WSN lifetime and charging efficiency remains a key research challenge.

Purpose of the Study:

• To propose an optimized charging strategy for WSNs utilizing a single, energy-limited MCD.
• To enhance network lifetime by prioritizing essential sensor nodes requiring the most support.
• To maximize the utilization of MCD energy for sustained network operation.

Main Methods:

• Developed an algorithm to identify the minimum set of sensor nodes crucial for maintaining network coverage and connectivity with minimal energy needs.
• Re-framed the network lifetime maximization problem to focus on optimal MCD energy allocation for these essential nodes.
• Designed adaptive charging algorithms based on MCD energy capacity relative to essential node energy requirements, balancing outage time and lifetime maximization.

Main Results:

• The proposed strategy significantly prolongs the network lifetime of WSNs.
• Simulation experiments demonstrate improved charging efficiency compared to existing methods.
• The algorithm effectively supports sensor nodes with the highest energy demands, ensuring network stability.

Conclusions:

• The novel charging strategy effectively addresses energy shortages in WSNs.
• Intelligent energy management of MCDs is crucial for maximizing WSN lifespan and performance.
• The proposed method offers a practical solution for extending the operational duration of wireless sensor networks.