Work place: Department of Computer Science, Umaru Ali Shinkafi Polytechnic, Sokoto, Nigeria
E-mail: us.tamba@gmail.com
Website: https://orcid.org/0009-0007-2867-9309
Research Interests:
Biography
Abubakar B. Tambawal Senior Lecturer Department of Computer Science at Umaru Ali Shinkafi
Polytechnic in Sokoto, Nigeria. He received his Ph.D. degree in computer science from university of Malaya,
kuala lumpur Malaysia. His research interests include mobile ad hoc networks and 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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