A Hybrid Mayfly-Aquila Optimization Algorithm Based Energy-Efficient Clustering Routing Protocol for Wireless Sensor...

Area of Science:

• Computer Science
• Electrical Engineering
• Network Engineering

Background:

• Wireless Sensor Networks (WSNs) face significant energy constraints due to battery-powered nodes, limiting network lifetime.
• Clustering is a key strategy to extend WSN longevity and reduce energy consumption by organizing nodes.
• Efficient Cluster Head (CH) selection and routing are critical for minimizing energy usage and maximizing network operational duration.

Purpose of the Study:

• To propose an energy-efficient clustering routing protocol for Wireless Sensor Networks (WSNs).
• To address the challenges of reducing energy consumption and extending the network lifetime in WSNs.
• To introduce a hybrid optimization algorithm for optimal Cluster Head (CH) selection and routing.

Main Methods:

• A hybrid Mayfly-Aquila optimization (MFA-AOA) algorithm is developed for WSN routing.
• The Mayfly algorithm is utilized for optimal Cluster Head (CH) selection among network nodes.
• The Aquila optimization algorithm is employed to determine the most efficient routes between CHs and the Base Station (BS).

Main Results:

• The proposed MFA-AOA protocol demonstrated superior energy efficiency compared to existing methods.
• Achieved reductions in energy consumption by 10.22%, 11.26%, and 14.28% in simulations.
• Showcased improvements in normalized energy by 9.56%, 11.78%, and 13.76% over state-of-the-art approaches.

Conclusions:

• The hybrid Mayfly-Aquila optimization algorithm offers a promising solution for energy-efficient routing in WSNs.
• The proposed protocol effectively extends WSN network lifetime by optimizing CH selection and data routing.
• This approach significantly enhances energy conservation, crucial for the practical deployment of WSNs.