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All Journal Vokasi UNESA Bulletin of Engineering, Technology and Applied Science
Matthew Iyobhebhe
Federal Polytechnic Nasarawa. Nigeria
Computer Science & IT Engineering Mechanical Engineering Transportation

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A Review on Energy Consumption Model on Hierarchical Clustering Techniques for IoT- based Multilevel Heterogeneous WSNs Using Energy Aware Node Selection Matthew Iyobhebhe; Abdooulie Momodou. S. Tekanyi; K. A. Abubilal; Aliyu. D Usman; H. A. Abdulkareem; Yau Isiaku; E. E Agbon; Elvis obi; Ishaya Chollom Botson; Chukwudi Ezugwu; Ridwan. O. Eleshin; Fatima Ashafa; Saba Abubakar; Abubakar Umar; Ajayi Ore-Ofe; Paul Thomas Muge
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 2 (2025)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v2i2.34882

Abstract

This review article scrutinizes the energy consumption model related to hierarchical clustering methods in IoT-based multi-tier heterogeneous networks (WSNs). Since energy efficiency is vital to prolong the operational activities of sensor nodes, this review article concentrated on energy-aware node selection as a significant technique for improving energy consumption. The review article deliberates on the challenges posed by dynamic wireless sensor network conditions, node heterogeneity like energy-based, and scalability challenges that affect energy management. This review article scrutinizes the energy consumption model related to hierarchical clustering methods in IoT-based multi-tier heterogeneous networks (WSNs). Since energy efficiency is vital to prolong the operational activities of sensor nodes, this review article concentrated on energy-aware node selection as a significant technique for improving energy consumption. We scrutinize different factors affecting efficient node selection, comprising residual energy, transmission distance, and sensor node reliability while juxtaposing these techniques with traditional node selection schemes. Furthermore, the importance of developed modeling techniques was highlighted. Finally, future research directions were outlined, by accentuating the incorporation of energy harvesting and collective models to improve the stability and operation of Wireless Sensor Networks. This holistic overview aims to offer appreciated insights for authors and practitioners in WSNs.
Consensus Optimization for Energy Efficiency in Heterogeneous Wireless Sensor Networks: Models, Techniques, and Future Directions Matthew Iyobhebhe; Abdoulie Momodou. S Tekanyi; Elvis Obi; Shamsudeen. A. Mikail; Botson Ishaya Chollom; Paul Thomas Muge; Athanisius Terlumun Utev; Ridwan. O Eleshin; Fatima Ashafa
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 3 No. 3 (2026): (In Progress)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

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Abstract

Energy efficiency continues to be a major concern in heterogeneous wireless sensor networks (HWSNs) due to unequal resource allocation and varying network dynamics. Consensus optimisation offers an effective paradigm for enabling distributed management and achieving balanced energy utilisation among heterogeneous sensor nodes. This review presents an in-depth examination of consensus-based models and techniques aimed at improving energy efficiency in HWSNs. It categorises existing methodologies based on their operational mechanisms and analyses how node heterogeneity impacts consensus formulation and overall network performance. In addition, it highlights key research limitations, including the lack of standardised classifications, inconsistent energy modelling, insufficient benchmarking, and limited analysis of the tradeoff between convergence and energy overhead. By synthesising advances in adaptive weighting, clustering mechanisms, and hierarchical consensus architectures, the study proposes future research pathways for scalable, robust, and energy-efficient consensus systems. Ultimately, this review provides a foundation for developing sustainable optimisation frameworks for next-generation sensor networks.
Co-Authors Abdooulie Momodou. S. Tekanyi Abdoulie Momodou. S Tekanyi Abubakar Umar Ajayi Ore-Ofe Aliyu. D Usman Athanisius Terlumun Utev Botson Ishaya Chollom Chukwudi Ezugwu E. E Agbon Elvis obi Elvis Obi Fatima Ashafa Fatima Ashafa H. A. Abdulkareem Ishaya Chollom Botson K. A. Abubilal Paul Thomas Muge Paul Thomas Muge Ridwan. O Eleshin Ridwan. O. Eleshin Saba Abubakar Shamsudeen. A. Mikail Yau Isiaku