COOP: A Computing and Offloading Algorithm for Unmanned Aerial Vehicle Assisted Terrestrial Networks

• Carlos Rocha UFPA
• Lucas Pacheco UFPA
• Lucas Bastos UFPA
• Denis Rosário UFPA
• Eduardo Cerqueira UFPA

DOI: https://doi.org/10.5753/sbrc_estendido.2024.2941

Abstract

Current wireless systems, such as 5G networks, have integrated Mobile Edge Computing (MEC) capabilities. Yet, they still face challenges in efficiently delivering such services to mobile users in dense and dynamic scenarios. This paper introduces COOP, an algorithm for optimizing Unmanned Aerial Vehicle (VANT)-assisted ground networks and providing connectivity and MEC services for mobile users. COOP employs a Genetic Algorithm (AG) to optimize VANT placement and service allocation for mobile users on the ground space. Results demonstrate that COOP outperforms existing approaches, showing reductions up to 33.3% and 41.3% in end-to-end delay compared to baseline algorithms in scenarios with 30, 50, and 100 mobile users.

References

Vehicular mobility trace of the city of cologne, germany [online]. [link]. Accessed: 2024-01-26.

Agarwal, B., Togou, M. A., Ruffini, M., and Muntean, G.-M. (2022). Qoe-driven optimization in 5g o-ran-enabled hetnets for enhanced video service quality. IEEE Communications Magazine, 61(1):56–62.

Akhtar et al. (2021). Managing chains of application functions over multi-technology edge networks. IEEE Transactions on Network and Service Management.

Cumino, P., Luís, M., Rosário, D., Cerqueira, E., and Sargento, S. (2023). On the use-fulness of flying base stations in 5g and beyond scenarios. Wireless Networks, pages 1–17.

Fan, X., Wu, P., and Xia, M. (2024). Air-to-ground communications beyond 5g: Uav swarm formation control and tracking. IEEE Trans. on Wireless Communications.

Guo, H., Wang, Y., Liu, J., and Liu, C. (2024). Multi-uav cooperative task offloading and resource allocation in 5g advanced and beyond. IEEE Trans. on Wireless Communications, 23(1):347–359.

Pacheco, L., Oliveira, H., Rosário, D., Zhao, Z., Cerqueira, E., Braun, T., and Mendes, P. (2021). Towards the future of edge computing in the sky: Outlook and future directions. In proceedings of the 17th International Conference on Distributed Computing in Sensor Systems (DCOSS), pages 220–227. IEEE.

Pandey, S. R., Kim, K., Alsenwi, M., Tun, Y. K., and Hong, C. S. (2021). A crowd-enabled task execution approach in uav networks towards fog computing. In proceedings of the IEEE International Conference on Big Data and Smart Computing (BigComp), pages 246–251. IEEE.

Rahman, M. H., Al-Naeem, M., Banerjee, A., and Sufian, A. (2023). Eeto-ga: Energy efficient trajectory optimization of uav-iot collaborative system using genetic algorithm. Applied Sciences, 13(4):2535.

Zhang, J., Tang, J., Feng, W., Zhang, X. Y., So, D. K. C., Wong, K.-K., and Chambers, J. (2024). Throughput maximization for ris-assisted uav-enabled wpcn. IEEE Access.

Zhao, Y., Zhang, W., Zhou, L., and Cao, W. (2021). A survey on caching in mobile edge computing. Wireless Communications and Mobile Computing, 2021:1–21.