An Energy-Efficient Routing Algorithm Based on Greedy Strategy for Energy Harvesting Wireless Sensor Networks.

Area of Science:

• Computer Science
• Electrical Engineering
• Networking

Background:

• Energy harvesting wireless sensor networks (EH-WSNs) are crucial for Internet of Things (IoT) development.
• Existing EH-WSN studies often neglect the interplay between energy status and data buffer limitations, leading to poor energy efficiency and high end-to-end delays.

Purpose of the Study:

• To propose a novel energy-efficient routing protocol for EH-WSNs that addresses the limitations of current approaches.
• To improve both energy efficiency and reduce end-to-end delay in EH-WSNs by integrating energy state and buffer management.

Main Methods:

• Developed an energy evaluation model incorporating energy harvesting, consumption, and classification to assess node energy status.
• Established a channel feature-based communication range judgment model to define node transmission areas.
• Designed a reception state adjustment mechanism considering buffer occupancy and MAC layer protocols to optimize data reception.

Main Results:

• The proposed greedy strategy-based routing algorithm demonstrated optimal performance in energy consumption, packet delivery ratio, average hop count, and end-to-end delay.
• The algorithm achieved acceptable performance regarding energy variance.

Conclusions:

• The novel routing protocol effectively balances energy harvesting, consumption, and data buffering for enhanced EH-WSN performance.
• The greedy strategy offers a promising solution for optimizing energy efficiency and reducing latency in IoT networks.