RCSS: A Real-Time On-Demand Charging Scheduling Scheme for Wireless Rechargeable Sensor Networks

Area of Science:

• Edge Computing
• Wireless Sensor Networks
• Energy Management

Background:

• Edge computing deployment involves numerous sensor nodes with dynamic energy consumption due to varying task burdens and environmental factors.
• Traditional periodic charging methods are insufficient for edge devices with fluctuating energy demands.
• Providing real-time, on-demand energy for edge devices presents a significant challenge in edge networks.

Purpose of the Study:

• To propose a real-time on-demand charging scheduling scheme (RCSS) for edge computing sensor nodes with limited mobile charger capacity.
• To address the dynamic energy consumption rates of individual nodes in edge networks.
• To enhance the operational longevity and efficiency of edge devices.

Main Methods:

• Developed a charging path construction algorithm considering dynamic node energy consumption.
• Introduced a next node selection algorithm for efficient charging.
• Implemented a charging circuit feasibility determination method.
• Utilized an adaptive charging threshold during the charging process to minimize node mortality.

Main Results:

• RCSS demonstrates superior performance compared to existing approaches.
• Achieved a higher number of surviving nodes.
• Improved average service time for edge devices.
• Enhanced overall charging efficiency.

Conclusions:

• The proposed RCSS effectively manages real-time, on-demand charging for edge computing sensor nodes.
• RCSS addresses the challenge of dynamic energy consumption in edge networks.
• The scheme significantly improves node survival rates, service time, and charging efficiency.