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Computing Challenges of UAV Networks: A Comprehensive Survey

Altaf Hussain1, Shuaiyong Li2, Tariq Hussain3, Xianxuan Lin4,*, Farman Ali5,*, Ahmad Ali AlZubi6

1 School of Computer Science & Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China
2 Key Laboratory of Industrial Internet of Things and Networked Control, Ministry of Education, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China
3 School of Computer Science and Technology, Zhejiang Gongshang University, Hangzhou, 310018, China
4 School of Artificial Intelligence, Nanjing University of Information Science & Technology, Nanjing, 210044, China
5 Department of Computer Science and Engineering, School of Convergence, College of Computing and Informatics, Sungkyunkwan University, Seoul, 03063, Republic of Korea
6 Department of Computer Science, Community College, King Saud University, Riyadh, 11495, Saudi Arabia

* Corresponding Authors: Xianxuan Lin. Email: email; Farman Ali. Email: email

Computers, Materials & Continua 2024, 81(2), 1999-2051. https://doi.org/10.32604/cmc.2024.056183

Abstract

Devices and networks constantly upgrade, leading to rapid technological evolution. Three-dimensional (3D) point cloud transmission plays a crucial role in aerial computing terminology, facilitating information exchange. Various network types, including sensor networks and 5G mobile networks, support this transmission. Notably, Flying Ad hoc Networks (FANETs) utilize Unmanned Aerial Vehicles (UAVs) as nodes, operating in a 3D environment with Six Degrees of Freedom (6DoF). This study comprehensively surveys UAV networks, focusing on models for Light Detection and Ranging (LiDAR) 3D point cloud compression/transmission. Key topics covered include autonomous navigation, challenges in video streaming infrastructure, motivations for Quality of Experience (QoE) enhancement, and avenues for future research. Additionally, the paper conducts an extensive review of UAVs, encompassing current wireless technologies, applications across various sectors, routing protocols, design considerations, security measures, blockchain applications in UAVs, contributions to healthcare systems, and integration with the Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL). Furthermore, the paper thoroughly discusses the core contributions of LiDAR 3D point clouds in UAV systems and their future prediction along with mobility models. It also explores the prospects of UAV systems and presents state-of-the-art solutions.

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Cite This Article

APA Style
Hussain, A., Li, S., Hussain, T., Lin, X., Ali, F. et al. (2024). Computing challenges of UAV networks: A comprehensive survey. Computers, Materials & Continua, 81(2), 1999-2051. https://doi.org/10.32604/cmc.2024.056183
Vancouver Style
Hussain A, Li S, Hussain T, Lin X, Ali F, AlZubi AA. Computing challenges of UAV networks: A comprehensive survey. Comput Mater Contin. 2024;81(2):1999-2051 https://doi.org/10.32604/cmc.2024.056183
IEEE Style
A. Hussain, S. Li, T. Hussain, X. Lin, F. Ali, and A.A. AlZubi, “Computing Challenges of UAV Networks: A Comprehensive Survey,” Comput. Mater. Contin., vol. 81, no. 2, pp. 1999-2051, 2024. https://doi.org/10.32604/cmc.2024.056183



cc Copyright © 2024 The Author(s). Published by Tech Science Press.
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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