Energy-efficient quad tree-based clustering using edge-assisted UAV-relay to enhance network lifetime in WSN

Area of Science:

• Computer Science
• Electrical Engineering
• Network Engineering

Background:

• Wireless sensor networks (WSNs) face critical challenges including high energy consumption, data loss, and limited network lifetime.
• Clustering in WSNs, while beneficial, often creates coverage and energy holes, leading to premature node failure.
• Existing WSNs struggle with efficient data transmission, impacting overall network performance and longevity.

Purpose of the Study:

• To maximize the network lifetime of wireless sensor networks.
• To minimize energy consumption during data transmission in WSNs.
• To address coverage and energy holes caused by clustering.

Main Methods:

• Proposed a novel architecture involving sensor nodes, an edge-assisted unmanned aerial vehicle (UAV), and a base station.
• Utilized an edge-assisted UAV to provide supplementary resources, thereby reducing energy demands for data transmission.
• Implemented enhanced communication strategies to boost data transmission speed and bandwidth, and reduce latency.

Main Results:

• Demonstrated significant reduction in energy consumption during data transmission.
• Achieved enhanced data transmission speed and bandwidth, leading to lower latency.
• Improved overall network performance and extended the network lifetime.

Conclusions:

• The integration of an edge-assisted UAV effectively mitigates energy consumption and extends WSN lifetime.
• Enhanced communication protocols significantly improve data transmission efficiency in WSNs.
• The proposed framework offers a viable solution for overcoming critical WSN challenges.