Enhancing network lifetime in WSNs through coot algorithm-based energy management model

Area of Science:

• Computer Science
• Network Engineering
• Optimization Algorithms

Background:

• Wireless Sensor Networks (WSN) face challenges including high energy consumption, communication delays, and security vulnerabilities.
• Existing optimization algorithms often struggle to balance these competing network performance metrics effectively.

Purpose of the Study:

• To propose a novel, energy-efficient clustering and routing technique for WSNs.
• To address critical issues of energy consumption, communication delay, and security in WSNs.
• To enhance overall network reliability and data integrity.

Main Methods:

• Developed a clustering and routing technique utilizing the Coot Optimization Algorithm (COA).
• Integrated an advanced fitness function evaluating cluster heads and routes based on residual energy, delay, security, trust, distance, and link quality.
• Compared COA against other metaheuristic algorithms (BOA, GA, TSO, GWO, BSA) via simulations.

Main Results:

• The proposed COA technique demonstrated superior performance compared to existing algorithms.
• Achieved the lowest communication delay and the highest network lifetime (3571 rounds).
• Showcased enhanced security (0.8) and trust (0.6) metrics with reduced energy consumption.

Conclusions:

• The Coot Optimization Algorithm offers an innovative and effective solution for improving WSN performance.
• The technique ensures even energy load distribution and maintains credible data flow.
• COA is highly suitable for WSN performance enhancement, offering significant improvements in efficiency, reliability, and security.