An improved LEACH algorithm integrated with Quantum Beluga Whale optimization for adaptive cluster configuration and...

Area of Science:

• Wireless Sensor Networks (WSNs)
• Network Routing Protocols
• Optimization Algorithms

Background:

• WSNs require energy-efficient routing due to network size and resource constraints.
• Conventional protocols like LEACH and LEACH-C have limitations in load balancing and energy efficiency.
• Existing hierarchical protocols struggle to optimize cluster formation and head rotation for prolonged network lifetime.

Purpose of the Study:

• To propose an enhanced LEACH protocol, QBWO-LEACH, for improved energy efficiency and network lifetime in WSNs.
• To leverage Quantum Beluga Whale Optimization (QBWO) for optimal cluster configuration and management.
• To enhance load balancing and energy distribution within the WSN.

Main Methods:

• A novel QBWO algorithm is integrated into the LEACH protocol's setup phase for centralized cluster organization.
• The algorithm determines cluster centroids, assigns members, and evaluates cluster parameters like energy and lifetime.
• A distributed cluster head rotation mechanism is employed using local member information for balanced energy distribution.

Main Results:

• QBWO-LEACH demonstrated superior comprehensive performance compared to traditional LEACH and its variants.
• Significant improvements were observed in node survival and network residual energy.
• Average improvements include 51.87% over LEACH, 17.69% over PF-LEACH, and 4.31% over GA2-LEACH.

Conclusions:

• The proposed QBWO-LEACH protocol effectively addresses the energy efficiency limitations of existing WSN routing protocols.
• QBWO-LEACH offers a robust solution for prolonging network lifetime and enhancing overall WSN performance.
• The integration of quantum computing principles with bio-inspired optimization shows promise for future WSN research.