An Enhanced Distributed Energy-Efficient Clustering Protocol with Improved Weighed Quantum Particle Swarm Optimization for Dynamic Cluster Allocation and Coordinated Transmission in WSN to Improve Performance Measures

International Journal of Electronics and Communication Engineering

© 2025 by SSRG - IJECE Journal

Volume 12 Issue 7

Year of Publication : 2025

Authors : S. Hilda, C. Kalaiselvi

10.14445/23488549/IJECE-V12I7P121

How to Cite?

S. Hilda, C. Kalaiselvi, "An Enhanced Distributed Energy-Efficient Clustering Protocol with Improved Weighed Quantum Particle Swarm Optimization for Dynamic Cluster Allocation and Coordinated Transmission in WSN to Improve Performance Measures," SSRG International Journal of Electronics and Communication Engineering, vol. 12,  no. 7, pp. 262-279, 2025. Crossref, https://doi.org/10.14445/23488549/IJECE-V12I7P121

Abstract:

This paper introduces an enhanced Distributed Energy-Efficient Clustering (DEEC) protocol combined with Improved Weighed Quantum Particle Swarm Optimization (IWQPSO) to address critical issues in Wireless Sensor Networks (WSNs), such as limited energy resources, uneven energy distribution, dynamic network conditions, and communication overhead. WSNs are vital for data collection and transmission in various applications, but their efficiency is hindered by these challenges. The proposed method leverages DEEC-IWQPSO for dynamic cluster allocation, optimizing the selection of CHs and cluster formations based on real-time network conditions like traffic load and resource availability. The integration of quantum principles in IWQPSO enhances the exploration and convergence speed of the optimization process, leading to more efficient resource utilization and energy management. The primary objectives are to improve energy efficiency, extend network lifetime, optimize data transmission, minimize communication overhead, and ensure scalability in large WSN environments. Simulation results demonstrate that the proposed DEEC-IWQPSO protocol reduces energy consumption by up to 35%, increases network lifetime by 30%, improves data transmission reliability by 25%, and reduces communication overhead by 20% compared to existing methods. These outcomes highlight the protocol's ability to provide a scalable and energy-efficient solution for WSNs, making it suitable for diverse, resource-constrained environments.

Keywords:

Wireless Sensor Networks, Distributed Energy-Efficient Clustering, Improved Weighed Quantum Particle Swarm Optimization, Dynamic cluster allocation, Energy efficiency, Network lifetime, Coordinated transmission, Data transmission efficiency, Resource optimization, Quantum optimization.

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