Extending Wireless Rechargeable Sensor Network Life without Full Knowledge.

Area of Science:

• Computer Science
• Wireless Communication
• Network Engineering

Background:

• Extending the operational life of Wireless Rechargeable Sensor Networks (WRSN) is crucial for their practical application and scalability.
• Current charging algorithms for WRSN often require complete prior knowledge of sensor node power levels, limiting their real-world adaptability.
• The growing size of WRSN presents significant challenges for efficient energy management and charging strategies.

Purpose of the Study:

• To develop a novel probabilistic algorithm for extending the lifespan of scalable WRSN.
• To enable efficient WRSN charging without requiring a priori knowledge of all sensor node power levels or complete network exploration.
• To enhance the practicality and adaptability of WRSN in dynamic, large-scale environments.

Main Methods:

• Development of a probabilistic algorithm that establishes a probability bound on sensor node power levels.
• Utilization of this probability bound to guide decision-making during WRSN exploration for charging.
• Simulation of a wireless power transfer unmanned aerial vehicle (UAV) to validate the algorithm's effectiveness in charging WRSN.

Main Results:

• The proposed probabilistic algorithm achieves, on average, 90% of the performance of optimal algorithms that require full network knowledge.
• The algorithm successfully extends the life of Wireless Rechargeable Sensor Networks without needing to explore the entire network.
• The charging strategy demonstrated insensitivity to a wide range of network parameter variations.

Conclusions:

• The developed probabilistic algorithm offers a scalable and efficient solution for charging Wireless Rechargeable Sensor Networks.
• Eliminating the need for full network exploration significantly enhances the adaptability and practicality of WRSN.
• This approach represents a significant advancement in energy management for large-scale wireless sensor networks.