Recent Routing Protocols in UAV Networks: Classifications, Challenges, and Future Directions

Year : 2026 | Volume : 04 | 02 | Page :
    By

    Ali H. Wheeb,

  1. Associate Professor, Department of Computer Engineering, College of Engineering, University of Baghdad, Baghdad, Iraq

Abstract

Routing protocols enable reliable communication in Unmanned Aerial Vehicle (UAV) networks, particularly Flying Ad-hoc Networks (FANETs), amid high-speed 3D mobility, dynamic topologies, and energy limits. Key challenges include intermittent links due to mobility, limited energy resources, variable network density, and the need to minimize end-to-end delay while maximizing throughput and fault tolerance. This paper classifies recent UAV routing protocols into topology-based routing protocols, position-based routing protocols, and hierarchical-based routing protocols. It reviews mechanisms, including predictive clustering and energy-aware metrics, addresses challenges like link failures and scalability, and compares performances via simulations, showing the superiority of hybrids in terms of throughput and packet delivery.

Keywords: UAV; FANETs; Routing Protocol; Topology Based Routing protocols; Position Based Routing Protocols; Hierarchical Based Routing Protocols

How to cite this article:
Ali H. Wheeb. Recent Routing Protocols in UAV Networks: Classifications, Challenges, and Future Directions. International Journal of Algorithms Design and Analysis Review. 2026; 04(02):-.
How to cite this URL:
Ali H. Wheeb. Recent Routing Protocols in UAV Networks: Classifications, Challenges, and Future Directions. International Journal of Algorithms Design and Analysis Review. 2026; 04(02):-. Available from: https://journals.stmjournals.com/ijadar/article=2026/view=250267


References

  1. A. Rozario, E. Ahmed, and N. Mansoor, “A Robust Routing Protocol in Cognitive Unmanned Aerial Vehicular Networks,” Sensors, vol. 24, no. 19, p. 6334, 2024.
  2. A. H. Wheeb, “Flying Ad hoc Networks (FANET): Performance Evaluation of Topology Based Routing Protocols,” Int. J. Interact. Mob. Technol., vol. 16, no. 4, pp. 137–149, 2022, doi: 10.3991/ijim.v16i04.28235.
  3. Z. Jia, S. He, Q. Zhu, W. Wang, Q. Wu, and Z. Han, “Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning,” arXiv Prepr. arXiv2508.00938, 2025.
  4. A. H. Wheeb, R. Nordin, A. A. Samah, M. H. Alsharif, and M. A. Khan, “Topology-Based Routing Protocols and Mobility Models for Flying Ad Hoc Networks : A Contemporary Review and Future Research Directions,” Drones, MDPI, vol. 6, no. 1, pp. 1–28, 2022, doi: https://doi.org/10.3390/drones6010009.
  5. S. Yang et al., “Hybrid ant colony-based inter-cluster routing protocol for FANET,” Sci. Rep., vol. 14, no. 1, p. 15632, 2024.
  6. M. Kaur, D. Prashar, L. Mrsic, and A. A. Khan, “Machine Learning-Based Routing Protocol in Flying Ad Hoc Networks: A Review.,” Comput. Mater. Contin., vol. 82, no. 2, 2025.
  7. H. Dong, B. Yu, and W. Wu, “Routing Protocol for Intelligent Unmanned Cluster Network Based on Node Energy Consumption and Mobility Optimization,” Sensors, vol. 25, no. 2, p. 500, 2025.
  8. O. S. Oubbati, A. Lakas, F. Zhou, M. Güneş, and M. B. Yagoubi, “A survey on position-based routing protocols for Flying Ad hoc Networks (FANETs),” Veh. Commun., vol. 10, pp. 29–56, 2017.
  9. G. Asaamoning and P. Mendes, “A Position-based Hybrid Routing Protocol for Clustered Flying Ad Hoc Networks,” Drones Auton. Veh., vol. 1, no. 2, p. 10001, 2024.
  10. M. C. Tho, N. T. H. Ly, L. H. Binh, and T. T. Vo, “QLR-FANET: A Q-learning and rate control-based routing protocol for flying ad hoc network,” ETRI J., 2025.
  11. [11]       K. Ben Samuel, S. D. Wolthusen, J. S. Otim, R. N. Akol, and M. Nsabagwa, “Routing protocols and Mobility Predictions for UAV Data Collection from Agricultural Sites: A Survey,” IEEE Access, 2025.
  12. M. J. Almansor et al., “Routing protocols strategies for flying Ad-Hoc network (FANET): Review, taxonomy, and open research issues,” Alexandria Eng. J., vol. 109, pp. 553–577, 2024.
  13. M. Jamalzadeh, M. Maadani, and M. Mahdavi, “EC-MOPSO: An edge computing-assisted hybrid cluster and MOPSO-based routing protocol for the Internet of Vehicles,” Ann. Telecommun., vol. 77, no. 7, pp. 491–503, 2022.
  14. A. Hussain and W. Ahmad, “Delay and Energy Aware Routing (DEAR) Protocol for UAV Networks,” ICCK Trans. Intell. Unmanned Syst., vol. 2, no. 1, pp. 1–14, 2025.
  15. M. Y. Arafat and S. Moh, “Routing Protocols for Unmanned Aerial Vehicle Networks: A Survey,” IEEE Access, vol. 7, pp. 498–516, 2019, doi: 10.1109/ACCESS.2018.2885539.
  16. J. W. Lim and Y.-B. Ko, “Q-learning based stepwise routing protocol for multi-uav networks,” in 2021 International Conference on Artificial Intelligence in Information and Communication (ICAIIC), 2021, pp. 307–309.
  17. X. Tan, Z. Zuo, S. Su, X. Guo, and X. Sun, “Research of security routing protocol for UAV communication network based on AODV,” Electronics, vol. 9, no. 8, p. 1185, 2020.
  18. A. H. Wheeb, R. Nordin, A. Samah, and D. Kanellopoulos, “Performance Evaluation of Standard and Modified OLSR Protocols for Uncoordinated UAV Ad-Hoc Networks in Search and Rescue Environments,” Electronics, vol. 12, no. 6, pp. 1–23, 2023, doi: https://doi.org/10.3390/electronics12061334.
  19. M. Al-Dabbagh, “Exploiting Conventional MANET Routing in UAV’s Based Environment,” J. Kufa Math. Comput., vol. 11, no. 2, pp. 12–17, 2024.
  20. S. Akter, D. V. A. Duong, D.-Y. Kim, and S. Yoon, “Task offloading and resource allocation in uav-aided emergency response operations via soft actor critic,” IEEE Access, vol. 12, pp. 69258–69275, 2024.
  21. Y. Lu et al., “UAV ad hoc network routing algorithms in space–air–ground integrated networks: Challenges and directions,” Drones, vol. 7, no. 7, p. 448, 2023.
  22. D. NR, “Challenges and Innovations in Routing for Flying Ad Hoc Networks: A Survey of Current Protocols.,” J. Comput. Anal. Appl., vol. 33, no. 2, 2024.
Ahead of Print Subscription Original Research
Volume 04
02
Received 17/03/2026
Accepted 02/04/2026
Published 20/07/2026
Publication Time 125 Days
43

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