Average Throughput Performance of Myopic Policy in Energy Harvesting Wireless Sensor Networks

Area of Science:

• Wireless Communication
• Sensor Networks
• Energy Harvesting

Background:

• Focuses on single-hop wireless sensor networks (WSNs) with M energy harvesting sensors.
• Sensors store harvested energy in infinite-capacity batteries.
• Fusion center lacks direct knowledge of sensor battery states or energy harvesting statistics.

Purpose of the Study:

• Investigate the average throughput of a Round-Robin type myopic policy.
• Analyze performance under an average reward (throughput) criterion.
• Determine conditions for policy optimality in energy harvesting WSNs.

Main Methods:

• Analytical and numerical investigation of a Round-Robin type myopic scheduling policy.
• Assumes data backlog, no battery leakage, and error-free communication.
• Considers sensor transmission only when scheduled and energy-sufficient.

Main Results:

• The Round-Robin policy's average throughput is analyzed.
• Optimality is demonstrated for specific classes of energy harvesting processes.
• Suboptimality is shown for a broader range of energy harvesting processes.

Conclusions:

• The Round-Robin policy offers a practical approach for WSN data scheduling.
• Performance is highly dependent on the characteristics of the energy harvesting process.
• Further research may explore adaptive policies for enhanced performance across diverse scenarios.