Abstract
Unmanned Aerial Vehicles (UAVs) have been widely used in both military and civilian scenarios since they are low in cost and flexible in use. They can adapt to a wide variety of dangerous scenarios and complete many tasks the Manned Aerial Vehicles (MAVs) can not undertake. In order to establish connectivity and collect data in large areas, numerous UAVs often cooperate with each other and set up a UAV wireless network. Many multi-hop routing protocols have been proposed to efficiently deliver messages with high delivery ratio and low energy consumption. However, most of them do not consider that the power level of UAVs is adjustable. In this paper, we propose a Power-Aware Routing (PAR) algorithm for UAV networks. PAR utilizes the pre-planned trajectory information of UAVs to compute the encounters at different power levels, and then constructs a power-aware encounter tree to calculate the transmission path with minimum energy consumption from the source to the destination within the delay constraint. Through extensive simulations, we demonstrate that compared with three classic algorithms, PAR significantly reduces the energy consumption and improves the network performance on the basis of ensuring timely delivery of packets.
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References
Asadpour, M., Hummel, K.A., Giustiniano, D., Draskovic, S.: Route or carry: motion-driven packet forwarding in micro aerial vehicle networks. IEEE Trans. Mob. Comput. 16(3), 843–856 (2016)
Fu, L., et al.: Joint optimization of multicast energy in delay-constrained mobile wireless networks. IEEE/ACM Trans. Networking 26(1), 633–646 (2018)
Hsu, Y.H., Gau, R.H.: Reinforcement learning-based collision avoidance and optimal trajectory planning in UAV communication networks. IEEE Trans. Mobile Comput. 1(1), 1–149 (2020)
Huang, H., Yin, H., Min, G., Zhang, J., Wu, Y., Zhang, X.: Energy-aware dual-path geographic routing to bypass routing holes in wireless sensor networks. IEEE Trans. Mob. Comput. 17(6), 1339–1352 (2017)
Kadadha, M., Otrok, H.: A blockchain-enabled relay selection for QoS-OLSR in urban VANET: a stackelberg game model. Ad Hoc Networks 117, 102502 (2021)
Keränen, A., Ott, J., Kärkkäinen, T.: The one simulator for DTN protocol evaluation. In: Proceedings of the 2nd International Conference on Simulation Tools and Techniques, pp. 1–10 (2009)
Li, X., Liu, L., Wang, L., Xi, J., Peng, J., Meng, J.: Trajectory-aware spatio-temporal range query processing for unmanned aerial vehicle networks. Comput. Commun. 178, 271–285 (2021)
Liu, C., Fang, D., Hu, Y., Tang, S., Xu, D., Cui, W., Chen, X., Liu, B., Xu, G., Chen, H.: Easygo: low-cost and robust geographic opportunistic sensing routing in a strip topology wireless sensor network. Comput. Netw. 143, 191–205 (2018)
Peng, J., Gao, H., Liu, L., Li, N., Xu, X.: TBM: an efficient trajectory-based multicast routing protocol for sparse UAV networks. In: 2020 IEEE 22nd International Conference on High Performance Computing and Communications; IEEE 18th International Conference on Smart City; IEEE 6th International Conference on Data Science and Systems (HPCC/SmartCity/DSS), pp. 867–872. IEEE (2020)
Peng, J., Gao, H., Liu, L., Wu, Y., Xu, X.: Fntar: a future network topology-aware routing protocol in UAV networks. In: 2020 IEEE Wireless Communications and Networking Conference (WCNC), pp. 1–6. IEEE (2020)
Zamalloa, M.Z., Seada, K., Krishnamachari, B., Helmy, A.: Efficient geographic routing over lossy links in wireless sensor networks. ACM Trans. Sens. Netw. (TOSN) 4(3), 1–33 (2008)
Zhang, G., Wu, Q., Cui, M., Zhang, R.: Securing UAV communications via joint trajectory and power control. IEEE Trans. Wirel. Commun. 18(2), 1376–1389 (2019)
Zhang, L., Hu, L., Hu, F., Ye, Z., Li, X., Kumar, S.: Enhanced OLSR routing for airborne networks with multi-beam directional antennas. Ad Hoc Networks 102, 102116 (2020)
Acknowledgment
This work is supported by the National Natural Science Foundation of China under No. U20B2050, Public Service Platform for Basic Software and Hardware Supply Chain Guarantee under No. TC210804A, the “National Key R &D Program of China” under No. 2021YFB2700500 and 2021YFB2700502.
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Zhai, W., Liu, L., Peng, J., Ding, Y., Lu, W. (2022). PAR: A Power-Aware Routing Algorithm for UAV Networks. In: Wang, L., Segal, M., Chen, J., Qiu, T. (eds) Wireless Algorithms, Systems, and Applications. WASA 2022. Lecture Notes in Computer Science, vol 13473. Springer, Cham. https://doi.org/10.1007/978-3-031-19211-1_28
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DOI: https://doi.org/10.1007/978-3-031-19211-1_28
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