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Metaheuristic Based Data Gathering Scheme for Clustered UAVs in 6G Communication Network

Ahmed S. Almasoud1, Siwar Ben Haj Hassine2, Nadhem NEMRI2, Fahd N. Al-Wesabi2,3, Manar Ahmed Hamza4,*, Anwer Mustafa Hilal4, Abdelwahed Motwakel4, Mesfer Al Duhayyim5

1 Department of Information Systems, College of Computer and Information Sciences, Prince Sultan University, Saudi Arabia
2 Department of Computer Science, College of Science & Arts at Mahayil, King Khalid University, Saudi Arabia
3 Faculty of Computer and IT, Sana'a University, Sana'a, Yemen
4 Department of Computer and Self Development, Preparatory Year Deanship, Prince Sattam bin Abdulaziz University, AlKharj, Saudi Arabia
5 Department of Natural and Applied Sciences, College of Community-Aflaj, Prince Sattam bin Abdulaziz University, Saudi Arabia

* Corresponding Author: Manar Ahmed Hamza. Email: email

Computers, Materials & Continua 2022, 71(3), 5311-5325. https://doi.org/10.32604/cmc.2022.024500

Abstract

The sixth-generation (6G) wireless communication networks are anticipated in integrating aerial, terrestrial, and maritime communication into a robust system to accomplish trustworthy, quick, and low latency needs. It enables to achieve maximum throughput and delay for several applications. Besides, the evolution of 6G leads to the design of unmanned aerial vehicles (UAVs) in providing inexpensive and effective solutions in various application areas such as healthcare, environment monitoring, and so on. In the UAV network, effective data collection with restricted energy capacity poses a major issue to achieving high quality network communication. It can be addressed by the use of clustering techniques for UAVs in 6G networks. In this aspect, this study develops a novel metaheuristic based energy efficient data gathering scheme for clustered unmanned aerial vehicles (MEEDG-CUAV). The proposed MEEDG-CUAV technique intends in partitioning the UAV networks into various clusters and assign a cluster head (CH) to reduce the overall energy utilization. Besides, the quantum chaotic butterfly optimization algorithm (QCBOA) with a fitness function is derived to choose CHs and construct clusters. The experimental validation of the MEEDG-CUAV technique occurs utilizing benchmark dataset and the experimental results highlighted the better performance over the other state of art techniques interms of different measures.

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APA Style
Almasoud, A.S., Hassine, S.B.H., NEMRI, N., Al-Wesabi, F.N., Hamza, M.A. et al. (2022). Metaheuristic based data gathering scheme for clustered uavs in 6G communication network. Computers, Materials & Continua, 71(3), 5311-5325. https://doi.org/10.32604/cmc.2022.024500
Vancouver Style
Almasoud AS, Hassine SBH, NEMRI N, Al-Wesabi FN, Hamza MA, Hilal AM, et al. Metaheuristic based data gathering scheme for clustered uavs in 6G communication network. Comput Mater Contin. 2022;71(3):5311-5325 https://doi.org/10.32604/cmc.2022.024500
IEEE Style
A.S. Almasoud et al., "Metaheuristic Based Data Gathering Scheme for Clustered UAVs in 6G Communication Network," Comput. Mater. Contin., vol. 71, no. 3, pp. 5311-5325. 2022. https://doi.org/10.32604/cmc.2022.024500



cc 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.
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