Energy-driven K-means-based LEACH routing protocol for enhanced lifetime in wireless sensor networks

Area of Science:

• Computer Science
• Electrical Engineering
• Network Engineering

Background:

• Wireless Sensor Networks (WSNs) are crucial for monitoring and automation but face limitations due to sensor node battery capacity.
• Traditional LEACH protocols use Euclidean distance for clustering, which inaccurately reflects communication energy costs.
• Existing energy-aware clustering schemes may introduce computational complexity.

Purpose of the Study:

• To propose an Energy-Driven K-Means-Based LEACH routing protocol that optimizes energy efficiency in WSNs.
• To enhance cluster head selection by replacing Euclidean distance with an energy-proxy metric.
• To improve network lifetime and performance without increasing computational overhead.

Main Methods:

• Developed a novel energy-proxy metric based on the Radio Energy Dissipation Model to replace Euclidean distance in K-means clustering.
• Implemented the Energy-Driven K-Means-Based LEACH protocol.
• Evaluated the protocol's performance against traditional K-means-Based LEACH and DEEC-KM through simulations.

Main Results:

• The proposed protocol achieved up to 16.98% improvement in network lifetime compared to K-means-Based LEACH.
• Consistently outperformed DEEC-KM in terms of lifetime, stability periods, delivered packets, and energy consumption across various network densities.
• Demonstrated significant gains in medium- and low-density networks, with comparable performance in dense deployments.

Conclusions:

• The Energy-Driven K-Means-Based LEACH protocol offers a lightweight, energy-aware enhancement to centralized LEACH clustering.
• The novel energy-proxy metric effectively favors low-energy links and penalizes long transmissions, improving cluster-head placement.
• The protocol successfully extends network lifetime and improves scalability for energy-constrained WSNs.