Internet of Things (IoT) is developing rapidly with wider application fields. IoT’s main infrastructure is called a wireless sensor network (WSN). Hence, WSN must be able to operate on various network models. Multi-hop clustering is considered a solution for adapting to various network sizes. Multi-hop clustering must be designed to maintain the balance of energy consumption between nodes, and many algorithms have been proposed for this purpose. However, most clustering algorithms are designed with the assumption that the network is a two-dimensional plane. In many applications, WSN is more appropriately modeled as a three-dimensional (3D) network, for example, the WSN application for structural health monitoring or underwater wireless sensor networks. Here, a clustering algorithm for 3D-WSN is proposed. This algorithm is developed based on an analysis of the balance of energy consumption, such that the network lifetime is expected to be longer. The main novelty of our algorithm is the utilization of multi-hop layered transmission. From the simulation, the performance of the proposed algorithm exhibits a good energy balance compared to an un-balanced analysis.

1. [1] G. Weston, “IoT Connectivity Industry Forecast by 2030,” 101 Blockchains, 2023. https://101blockchains.com/iot-connectivity-industry-forecast/ [Accessed July 22, 2023]
2. [2] X. Zhao et al., “Design and Implementation of Environmental Monitoring System Based on Multi-Protocol Fusion Internet of Things,” J. Adv. Comput. Intell. Intell. Inform., Vol.26, No.5, pp. 715-721, 2022. https://doi.org/10.20965/jaciii.2022.p0715
3. [3] Y. Fujinawa, R. Kouda, and Y. Noda, “The Resilient Smart City (An Proposal),” J. Disaster Res., Vol.10, No.2, pp. 319-325, 2015. https://doi.org/10.20965/jdr.2015.p0319
4. [4] J. Zhang and M. Wang, “Research on Communication Scheduling Algorithm for Smart Home in Internet of Things Under Cloud Computing,” J. Adv. Comput. Intell. Intell. Inform., Vol.23, No.1, pp. 124-128, 2019. https://doi.org/10.20965/jaciii.2019.p0124
5. [5] S. Teruhi, Y. Yamaguchi, and J. Akahani, “Water Leakage Detection System for Underground Pipes by Using Wireless Sensors and Machine Learning,” J. Disaster Res., Vol.12, No.3, pp. 557-568, 2017. https://doi.org/10.20965/jdr.2017.p0557
6. [6] K. Kerrigan and G. E. O’Donnell, “Temperature Measurement in CFRP Milling Using a Wireless Tool-Integrated Process Monitoring Sensor,” Int. J. Automation Technol., Vol.7, No.6, pp. 742-750, 2013. https://doi.org/10.20965/ijat.2013.p0742
7. [7] H. Jing, “Node Deployment Algorithm Based on Perception Model of Wireless Sensor Network,” Int. J. Autom. Technol., Vol.9, No.3, pp. 210-215, 2015. https://doi.org/10.20965/ijat.2015.p0210
8. [8] S. Siddiqui et al., “Toward Software-Defined Networking-Based IoT Frameworks: A Systematic Literature Review, Taxonomy, Open Challenges and Prospects,” IEEE Access, Vol.10, pp. 70850-70901, 2022. https://doi.org/10.1109/ACCESS.2022.3188311
9. [9] U. Uyoata, J. Mwangama, and R. Adeogun, “Relaying in the Internet of Things (IoT): A Survey,” IEEE Access, Vol.9, pp. 132675-132704, 2021. https://doi.org/10.1109/ACCESS.2021.3112940
10. [10] D. Abruzzese et al., “IoT sensors for modern structural health monitoring. A new frontier,” Procedia Struct. Integr., Vol.25, pp. 378-385, 2020. https://doi.org/10.1016/j.prostr.2020.04.043
11. [11] K. M. Awan et al., “Underwater Wireless Sensor Networks: A Review of Recent Issues and Challenges,” Wirel. Commun. Mob. Comput., Vol.2019, Article No.e6470359, 2019. https://doi.org/10.1155/2019/6470359
12. [12] W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energy-efficient communication protocol for wireless microsensor networks,” Proc. of the 33rd Annual Hawaii Int. Conf. on System Sciences, Vol.2, 2000. https://doi.org/10.1109/HICSS.2000.926982
13. [13] A. A. Abbasi and M. Younis, “A survey on clustering algorithms for wireless sensor networks,” Comput. Commun., Vol.30, Nos.14-15, pp. 2826-2841, 2007. https://doi.org/10.1016/j.comcom.2007.05.024
14. [14] A. Shahraki, A. Taherkordi, Ø. Haugen, and F. Eliassen, “Clustering objectives in wireless sensor networks: A survey and research direction analysis,” Comput. netw., Vol.180, Article No.107376, 2020. https://doi.org/10.1016/j.comnet.2020.107376
15. [15] I. Daanoune, B. Abdennaceur, and A. Ballouk, “A comprehensive survey on LEACH-based clustering routing protocols in Wireless Sensor Networks,” Ad Hoc Netw., Vol.114, Article No.102409, 2021. https://doi.org/10.1016/j.adhoc.2020.102409
16. [16] A. Shahraki, A. Taherkordi, Ø. Haugen, and F. Eliassen, “A survey and future directions on clustering: From WSNs to IoT and modern networking paradigms,” IEEE Trans. Netw. Serv. Manag., Vol.18, No.2, pp. 2242-2274, 2021. https://doi.org/10.1109/TNSM.2020.3035315
17. [17] M. S. Batta, H. Mabed, Z. Aliouat, and S. Harous, “A distributed multi-hop intra-clustering approach based on neighbors two-hop connectivity for IoT networks,” Sensors, Vol.21, No.3, Article No.873, 2021. https://doi.org/10.3390/s21030873
18. [18] A. Suharjono, Wirawan, and G. Hendrantoro, “A new unequal clustering algorithm using energy-balanced area partitioning for wireless sensor networks,” Int. J. Smart Sens. Intell. Syst., Vol.6, No.5, pp. 1808-1829, 2013. https://doi.org/10.21307/ijssis-2017-616
19. [19] Z. Zhao, D. Shi, G. Hui, and X. Zhang, “An energy-optimization clustering routing protocol based on dynamic hierarchical clustering in 3D WSNs,” IEEE Access, Vol.7, pp. 80159-80173, 2019. https://doi.org/10.1109/ACCESS.2019.2923882
20. [20] Y. Xu, W. Jiao, and M. Tian, “An energy-efficient routing protocol for 3D wireless sensor networks,” IEEE Sens. J., Vol.21, No.17, pp. 19550-19559, 2021. https://doi.org/10.1109/JSEN.2021.3086806