Samaila Buda

Work place: Physics Depatment, Usmanu Danfodiyo University, Sokoto, Nigeria

E-mail: samaila.buda@udusok.edu.ng

Website: https://orcid.org/0000-0002-0584-3918

Research Interests:

Biography

Samila Buda is an Associate Professor in the Department of Physics at Usmanu Danfodiyo University Sokoto,
Nigeria. He received his Ph.D. degree in physics from university of putra malaysia. His research interests
include photovoltaic and energy efficiency.

Author Articles
An Adaptive Energy-Aware Clustering Algorithm for Lifetime Maximization in Homogeneous Wireless Sensor Networks

By Ishaq A. Idris Abdulkarim Bello Abubakar B. Tambawal Samaila Buda

DOI: https://doi.org/10.5815/ijwmt.2026.02.07, Pub. Date: 8 Apr. 2026

Wireless Sensor Networks have emerged as a key technology enabling real time data collection and monitoring across various domains, including environmental monitoring, industrial control, healthcare, and security applications. However, despite their growing relevance, energy efficiency remains a fundamental design challenge due to the limited power supply of sensor nodes, which directly impacts overall network lifetime and reliability. This paper proposes an Adaptive Energy-Aware Clustering Protocol (EACP) designed to improve energy efficiency and extend the operational lifetime of homogeneous WSNs. The proposed protocol integrates three main mechanisms: Residual Energy-based Cluster Head Selection, to ensure balanced energy distribution; Mobility-Aware Cluster Head Reassignment, to maintain stable communication under node mobility; and Base Station Proximity Based Direct Transmission, which allows nodes near the BS to bypass CHs, thereby minimizing redundant energy use. These mechanisms allow the network to dynamically adapt to changing energy conditions and communication distances. The protocol was evaluated through extensive MATLAB simulations and compared with benchmark protocols including LEACH, HAC, and HSA. Simulation results demonstrate that the proposed EACP significantly improves network performance. Specifically, it achieves 50% to 94% improvement in network lifetime, reduces energy consumption by approximately 20% to 25%, and increases throughput by more than 2.5 times compared to the benchmark protocols. These results demonstrate that EACP offers a scalable, energy-efficient communication strategy well suited for large scale WSNs deployments.

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