Multi-Tier Cluster Based Energy Conservative Wireless Sensor Networks
DOI:
https://doi.org/10.29284/q133y603Keywords:
cluster heads, network lifetime, routing protocols, wireless sensor networks, energy efficiency, tier networks.Abstract
The Wireless Sensor Network (WSN) is made up of numerous nodes that are dispersed at random both close to and far from the base station. Forwarding data generated by remote nodes adds to the communication burdens of the nodes closer to the Base Station (BS). As a result, they lose energy quickly and pass away more quickly than remote nodes. Clustering, multi-hop routing, and two-tier networks that combine evolutionary and classical methods were proposed by several authors as ways to extend the lifetime of networks. Hence, nodes close to or distant from the BS will need to choose shorter pathways for transmission instead of their assigned ones. Thus, depending on their topologies, such as two-tier or three-tier networks, it is possible to guarantee, to some extent, minimal power consumption per bit of transmission. This article has built four-tier networks to further boost lifetime. In addition to increasing the network's lifetime, improved its stability compared to earlier networks by keeping the nodes' energy dissipation uniform. All issues considered, the simulation results show that the proposed networks are superior to the two- and three-tiered networks. Additionally, WSNs' heterogeneous networks were incorporated into this four-tiered network design.
References
[1]. N. Moussa, Z. Hamidi-Alaoui, El. Belrhiti and A. Alaoui, “ECRP: an energy-aware cluster-based routing protocol for wireless sensor networks”, Wireless Networks, Vol. 26, 2020, pp. 2915-2928.
[2]. Z. Wang , H. Ding , Li B, L. Bao, Z. Yang and Q. Liu, “Energy efficient cluster based routing protocol for WSN using firefly algorithm and ant colony optimization”, Wireless Personal Communications. Vol. 125, no. 3, 2022, pp. 2167-2200.
[3]. A. D. Gupta and R. K. Rout, “An effective optimization method for energy efficient clustering in EH wireless sensor networks”, in Proc International Conference on Technological Advancements and Innovations (ICTAI), 2021, pp. 699-702.
[4]. R. Dogra, S. Rani, B. Sharma, S. Verma, D. Anand and P. Chatterjee, “A novel dynamic clustering approach for energy hole mitigation in Internet of Things-based wireless sensor network”, International Journal of Communication Systems, Vol. 34, No. 9, 2021, pp. e4806.
[5]. B. M. Sahoo, H. M. Pandey and T. Amgoth, “GAPSO-H: A hybrid approach towards optimizing the cluster based routing in wireless sensor network”, Swarm Evolution Computation, Vol. 60, 2021, pp. 100772.
[6]. R. Priyadarshi, “Energy-Efficient Routing in Wireless Sensor Networks: A Meta-heuristic and Artificial Intelligence-based Approach: A Comprehensive Review”, Archives of Computational Methods in Engineering, Vol. 31, 2024, pp. 2109–2137.
[7]. A. Sisodia, S. Vishnoi and S. Upadhyay, “Enhancing energy efficiency: a protocol assessment in multi-hop mesh-based IOUT networks”, Multimedia Tools and Applications, 2024.
[8]. S. H. Kang, “Energy optimization in cluster-based routing protocols for large-area wireless sensor networks”, Symmetry, Vol.11, No.1, 2019, pp. 37.
[9]. R. E. Mohamed, A. I. Saleh, M. Abdelrazzak and A. S. Samra, “Survey on wireless sensor network applications and energy efficient routing protocols”, Wireless Personal Communications. Vol. 101, 2018, pp. 1019-1055.
[10]. D. WohweSambo, B. O. Yenke, A. Förster and P. Dayang, “Optimized clustering algorithms for large wireless sensor networks: A review”, Sensors, Vol. 19, No. 2, 2019, pp. 322.
[11]. K. Guleria, A. K. Verma, “Comprehensive review for energy efficient hierarchical routing protocols on wireless sensor networks”, Wireless Networks, Vol. 25, 2019. pp. 1159-1183.
[12]. H. Shukun, Li. QinlinKhishe, Mohammad Salih Mohammed, Amin Mohammadi, Hassan and Mohammadi Mokhtar, “The optimization of nodes clustering and multi-hop routing protocol using hierarchical chimp optimization for sustainable energy efficient underwater wireless sensor networks”, Wireless Networks, Vol. 30. 2024, pp. 233–252.
[13]. Mohammad Ali Rezaii , Majid Azhdari , Azar Mahmood zadeh and Mohammad Khishe, “Power Consumption Optimization in Underwater Wireless Sensor Networks Based on EECRU Clustering Algorithm for Routing”, Iranian Journal of Marine Science And Technology, Vol. 24 No. 95, 2020, pp. 1-10.
[14]. G. R. Asha and Gowrishankar, “Energy efficient clustering and routing in a wireless sensor networks”, Procedia Computer Science, Vol. 134, 2018, pp. 178-185.
[15]. Ved Prakash,and Suman Pandey, “Metaheuristic algorithm for energy efficient clustering scheme in wireless sensor networks”, Microprocessors and Microsystems, Vol. 101, 2023, pp. 104898.
[16]. F. Kiani et al, “EEAR: An energy effective-accuracy routing algorithm for wireless sensor networks”, Life Science Journal, Vol. 10, 2013, pp. 39-45.
[17]. V. Tekulapally, D. Chali, and T. A. Abose, “An energy optimization clustering methods for homogeneous networks of wireless sensors”, in Proc Communications in Computer and Information Science, Springer 2024, pp. 32–42.
[18]. T. A. Abose, V. Tekulapally, K. T. Megersa, D. C. Kejela, S. T. Daka, and K. A. Jember, “Improving wireless sensor network lifespan with optimized clustering probabilities, improved residual energy LEACH and energy efficient LEACH for corner-positioned base stations”, Heliyon, Vol. 10, 2024, pp. e34382.
[19]. T. A. Abose, V. Tekulapally, D. C. Kejela, K. T. Megersa, S. T. Daka, and K. A. Jember, “Optimized cluster routing protocol with energysustainable mechanisms for wireless sensor networks”, IEEE Access, Vol. 12, 2024, pp. 99661–99671.
[20]. T A. Abose, V. Tekulapally, S. T. Daka, D. C. Kejela, A. E. Duguma and D. T. Degaga, “Improved Energy Efficient Anytime Optimistic Algorithm for PEGASIS to Extend Network Lifetime in Homogeneous and Heterogeneous Networks”, IEEE Access, Vol. 13, 2025, pp. 110012-110029.
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This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

