Energy Efficient Data Transmission for Sensors with Wireless Charging.

Area of Science:

• Wireless communication
• Energy harvesting
• Sensor networks

Background:

• Sensors require efficient energy management for data transmission.
• Periodic wireless charging presents unique challenges due to thermal effects.
• Optimizing energy utilization is crucial for prolonged sensor operation.

Purpose of the Study:

• To maximize energy utilization for data transmission in sensors with periodic wireless charging.
• To analyze the impact of thermal effects on energy efficiency.
• To develop algorithms for both limited and extended wireless charging scenarios.

Main Methods:

• Analysis of two distinct problem classes: limited and extended wireless charging periods.
• Development of algorithms to address each problem class.
• Derivation of performance bounds for the proposed algorithms.

Main Results:

• An algorithm for limited charging provides a performance bound of (1 - 1/2m)(OPT - E).
• An algorithm for extended charging achieves a performance bound of 2m/(2m-1)OPT + 1.
• Simulations validate the theoretical analysis of the algorithms.

Conclusions:

• The proposed algorithms effectively maximize sensor energy utilization under periodic wireless charging.
• Thermal effects are successfully integrated into the energy optimization framework.
• The study provides quantifiable performance bounds for practical sensor network applications.