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Vol. 11, No. 2, May 2026

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Performance Analysis of Cluster-based Multi-UAV Routing Protocol under Various Mobility Models using NS-3

https://doi.org/10.22219/kinetik.v11i2.2507
Harry Darmawan
Politeknik Elektronika Negeri Surabaya
Prima Kristalina
Politeknik Elektronika Negeri Surabaya
Moch. Zen Samsono Hadi
Politeknik Elektronika Negeri Surabaya

Corresponding Author(s) : Prima Kristalina

prima@pens.ac.id

Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, Vol. 11, No. 2, May 2026

Abstract

In this paper, the performance of a cluster-based multi-UAV communication system is analyzed as a means to enhance network reliability and coordination in support of Search and Rescue (SAR) operations within disaster-affected areas. The proposed approach addresses the challenges of maintaining connectivity, ensuring efficient data transmission, and facilitating effective collaboration among UAVs in critical environments. The system is designed with a four-layer architecture: Base Station (BS), Cluster Head (CH), Clustered Drone (CD), and User Equipment (UE). These layers are modeled and evaluated using Network Simulator 3 (NS-3). Three routing protocols, namely OLSR, AODV, and DSDV are evaluated under three types of UAV mobility models: Gauss-Markov, Random Waypoint (RWP), and Reference Point Group Mobility (RPGM). Quality of Service (QoS) parameters for wireless networks, such as throughput, packet delivery ratio (PDR), delay, and packet loss, are analyzed under several cluster-based UAV scenarios. The simulation results show that the cluster-based multi-UAV model using OLSR routing protocol achieves the best performance under the RPGM mobility model, with an average throughput of 67.57 kbps, 87.47% PDR, 86 ms delay, and 12.53% packet loss, outperforming the other routing protocols. The OLSR routing protocol demonstrates the highest consistency, with higher throughput and PDR values, as well as lower delay and packet loss compared to AODV and DSDV, particularly in small- to medium-scale node densities. This research contributes to the development of UAV-based cluster communication systems, particularly in terms of efficiency, stability, and adaptability to dynamic disaster environments.

Keywords

Clustered-based Multi-UAV Inter-UAV Communication System NS-3 Routing Protocol Mobility Model QoS
Darmawan, H., Kristalina, P., & Samsono Hadi, M. Z. . (2026). Performance Analysis of Cluster-based Multi-UAV Routing Protocol under Various Mobility Models using NS-3. Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control, 11(2), 249-258. https://doi.org/10.22219/kinetik.v11i2.2507
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References
  1. M. Lyu, Y. Zhao, C. Huang, and H. Huang, “Unmanned Aerial Vehicles for Search and Rescue: A Survey,” Remote Sens. (Basel)., vol. 15, no. 13, p. 3266, Jun. 2023, https://doi.org/10.3390/rs15133266
  2. A. Villarino, H. Valenzuela, N. Antón, M. Domínguez, and X. C. Méndez Cubillos, “UAV Applications for Monitoring and Management of Civil Infrastructures,” May 01, 2025, Multidisciplinary Digital Publishing Institute (MDPI). https://doi.org/10.3390/infrastructures10050106
  3. H. Shakhatreh et al., “Unmanned Aerial Vehicles: A Survey on Civil Applications and Key Research Challenges,” Apr. 2018, https://doi.org/10.1109/ACCESS.2019.2909530
  4. E. T. Alotaibi, S. S. Alqefari, and A. Koubaa, “LSAR: Multi-UAV Collaboration for Search and Rescue Missions,” IEEE Access, vol. 7, pp. 55817–55832, 2019, https://doi.org/10.1109/ACCESS.2019.2912306
  5. J. Zhou, J. Yang, and L. Lu, “Research on Multi-UAV Networks in Disaster Emergency Communication,” in IOP Conference Series: Materials Science and Engineering, Institute of Physics Publishing, Jan. 2020. https://doi.org/10.1088/1757-899X/719/1/012054
  6. I. Chandran and K. Vipin, “Multi-UAV networks for disaster monitoring: challenges and opportunities from a network perspective,” Jan. 01, 2024, Canadian Science Publishing. https://doi.org/10.1139/dsa-2023-0079
  7. H. N. Dianti, M. Z. S. Hadi, A. Pratiarso, and P. Kristalina, “Multihop Communication System in 2D and 3D Environments on WSN for Disaster Applications using NS-3,” in IES 2022 - 2022 International Electronics Symposium: Energy Development for Climate Change Solution and Clean Energy Transition, Proceeding, Institute of Electrical and Electronics Engineers Inc., 2022, pp. 272–277. https://doi.org/10.1109/IES55876.2022.9888357
  8. M. Y. Arafat, M. A. Habib, and S. Moh, “Routing protocols for UAV-aided wireless sensor networks,” Jun. 01, 2020, MDPI AG. https://doi.org/10.3390/APP10124077
  9. S. Ur Rahman, G. H. Kim, Y. Z. Cho, and A. Khan, “Positioning of UAVs for throughput maximization in software-defined disaster area UAV communication networks,” Journal of Communications and Networks, vol. 20, no. 5, pp. 452–463, Oct. 2018, https://doi.org/10.1109/JCN.2018.000070
  10. A. Joshi, A. K. Singh, and M. Yadav, “Optimizing FANET Performance using Realistic Mobility Model,” in 2024 15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024, Institute of Electrical and Electronics Engineers Inc., 2024. https://doi.org/10.1109/ICCCNT61001.2024.10724233
  11. Y. Bai et al., “A Deep Learning Approach for Wireless Network Performance Classification Based on UAV Mobility Features,” Drones, vol. 7, no. 6, Jun. 2023, https://doi.org/10.3390/drones7060377
  12. A. Kurniawan, P. Kristalina, and M. Z. S. Hadi, “Performance Analysis of Routing Protocols AODV, OLSR and DSDV on MANET using NS3,” in IES 2020 - International Electronics Symposium: The Role of Autonomous and Intelligent Systems for Human Life and Comfort, Institute of Electrical and Electronics Engineers Inc., Sep. 2020, pp. 199–206. https://doi.org/10.1109/IES50839.2020.9231690
  13. A. H. Wheeb, R. Nordin, A. 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 (Switzerland), vol. 12, no. 6, Mar. 2023, https://doi.org/10.3390/electronics12061334
  14. M. Tahboush, M. Adawy, and O. Aloqaily, “PEO-AODV: Preserving Energy Optimization Based on Modified AODV Routing Protocol for MANET,” International Journal of Advances in Soft Computing and its Applications, vol. 15, no. 2, pp. 263–277, 2023, https://doi.org/10.15849/IJASCA.230720.18
  15. I. U. Khan, M. A. Hassan, M. Fayaz, J. Gwak, and M. A. Aziz, “Improved sequencing heuristic DSDV protocol using nomadic mobility model for FANETS,” Computers, Materials and Continua, vol. 70, no. 2, pp. 3653–3666, 2022, https://doi.org/10.32604/cmc.2022.020697
  16. A. R. Fadhila, M. Z. S. Hadi, and P. Kristalina, “3-Dimensional Static Environment Multihop Communication System for SAR Team,” in IES 2022 - 2022 International Electronics Symposium: Energy Development for Climate Change Solution and Clean Energy Transition, Proceeding, Institute of Electrical and Electronics Engineers Inc., 2022, pp. 261–266. https://doi.org/10.1109/IES55876.2022.9888387
  17. A. F. M. S. Shah, “Architecture of Emergency Communication Systems in Disasters through UAVs in 5G and Beyond,” Drones, vol. 7, no. 1, Jan. 2023, https://doi.org/10.3390/drones7010025
  18. A. Mehmood, Z. Iqbal, A. A. Shah, C. Maple, and J. Lloret, “An Intelligent Cluster-Based Communication System for Multi-Unmanned Aerial Vehicles for Searching and Rescuing,” Electronics (Switzerland), vol. 12, no. 3, Feb. 2023, https://doi.org/10.3390/electronics12030607
  19. S. Mokhtari, N. Nouri, J. Abouei, A. Avokh, and K. N. Plataniotis, “Relaying Data With Joint Optimization of Energy and Delay in Cluster-Based UAV-Assisted VANETs,” IEEE Internet Things J., vol. 9, no. 23, pp. 24541–24559, Dec. 2022, https://doi.org/10.1109/JIOT.2022.3188563
  20. N. Zhang, F. Nex, G. Vosselman, and N. Kerle, “Training a Disaster Victim Detection Network for UAV Search and Rescue Using Harmonious Composite Images,” Remote Sens. (Basel)., vol. 14, no. 13, Jul. 2022, https://doi.org/10.3390/rs14132977
  21. H. Koumaras et al., “5g-enabled uavs with command and control software component at the edge for supporting energy efficient opportunistic networks,” Energies (Basel)., vol. 14, no. 5, Mar. 2021 https://doi.org/10.3390/en14051480
  22. J. Viana, F. Cercas, A. Correia, R. Dinis, and P. Sebastião, “MIMO relaying UAVs operating in public safety scenarios,” Drones, vol. 5, no. 2, 2021, https://doi.org/10.3390/drones5020032
  23. X. Chen, J. Tang, and S. Lao, “Review of unmanned aerial vehicle swarm communication architectures and routing protocols,” Applied Sciences (Switzerland), vol. 10, no. 10, May 2020, https://doi.org/10.3390/app10103661
  24. V. S. Widhi Prabowo, A. Fahmi, N. M. Adriansyah, and N. Andini, “Energy efficient resources allocations for wireless communication systems,” Telkomnika (Telecommunication Computing Electronics and Control), vol. 17, no. 4, pp. 1625–1634, Aug. 2019, https://doi.org/10.12928/TELKOMNIKA.V17I4.10135
  25. Z. Cui, K. Guan, C. Oestges, C. Briso-Rodriguez, B. Ai, and Z. Zhong, “Cluster-Based Characterization and Modeling for UAV Air-to-Ground Time-Varying Channels,” IEEE Trans. Veh. Technol., vol. 71, no. 7, pp. 6872–6883, Jul. 2022, https://doi.org/10.1109/TVT.2022.3168073
  26. V. Kumar, R. K. Dwivedi, and S. Prakash, “An Improved Gauss-Markov Mobility Model for FANET using NS3 Simulation in 3-Dimension Environment,” in 2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023, Institute of Electrical and Electronics Engineers Inc., 2023. https://doi.org/10.1109/ICCCNT56998.2023.10307875
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