Abstract
With high mobility and adaptability, the Unmanned Aerial Vehicle (UAV) has provided a promising solution for data collection in Wireless Sensor Networks (WSNs). However, few existing works considered that data overwritten would occur if the UAV can not collect data from sensors in time, which will cause data loss in WSNs. Moreover, the importance of data stored in different sensors may vary significantly according to the application scenario. In this paper, we formulate a novel Loss Minimization Problem (LMP) in a UAV-enabled WSN. The objective is to minimize the volume of weighted data loss in the WSN by jointly considering the UAV hovering locations and hovering durations, subject to the limited energy capacity. We first devise a novel one-to-many data collection scheme that enables the UAV to collect data from multiple sensors simultaneously. Then we discrete the infinite hovering locations of the UAV into finite to reduce computational complexity. We instead propose efficient heuristic and approximation algorithms for the optimization problem. Finally, we evaluate the performance of the proposed algorithms through extensive experimental simulations. Simulation results demonstrated that the proposed algorithms are promising.
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References
Chen, M., Liang, W., Li, J.: Energy-efficient data collection maximization for UAV-assisted wireless sensor networks. In: 2021 19th IEEE Wireless Communications and Networking Conference (WCNC), pp. 1–7. IEEE (2021)
Engels, C., Manthey, B.: Average-case approximation ratio of the 2-opt algorithm for the TSP. Oper. Res. Lett. 37(2), 83–84 (2009)
Englert, M., Röglin, H., Vöcking, B.: Worst case and probabilistic analysis of the 2-Opt algorithm for the TSP. Algorithmica 68(1), 190–264 (2013). https://doi.org/10.1007/s00453-013-9801-4
Guo, J., Wang, T., He, Y., Jin, M., Jiang, C., Liu, Y.: TwinLeak: RFID-based liquid leakage detection in industrial environments. In: 2019 38th IEEE International Conference on Computer Communications (INFOCOM), pp. 883–891. IEEE (2019)
Li, Y., et al.: Data collection maximization in IoT-sensor networks via an energy-constrained UAV. IEEE Trans. Mob. Comput. (2021)
Liang, Y., et al.: Nonredundant information collection in rescue applications via an energy-constrained UAV. IEEE Internet Things J. 6(2), 2945–2958 (2018)
Liu, T., Wu, B., Zhang, S., Peng, J., Xu, W.: An effective multi-node charging scheme for wireless rechargeable sensor networks. In: 2020 39th IEEE International Conference on Computer Communications (INFOCOM), pp. 2026–2035. IEEE (2020)
Luo, C., Satpute, M.N., Li, D., Wang, Y., Chen, W., Wu, W.: Fine-grained trajectory optimization of multiple UAVs for efficient data gathering from WSNs. IEEE/ACM Trans. Networking 29(1), 162–175 (2020)
Mozaffari, M., Saad, W., Bennis, M., Debbah, M.: Mobile internet of things: can UAVs provide an energy-efficient mobile architecture? In: 2016 IEEE Global Communications Conference (GLOBECOM), pp. 1–6 (2016)
Qin, Z., Li, A., Dong, C., Dai, H., Xu, Z.: Completion time minimization for multi-UAV information collection via trajectory planning. Sensors 19(18), 4032 (2019)
Qin, Z., et al.: Task selection and scheduling in UAV-enabled MEC for reconnaissance with time-varying priorities. IEEE Internet Things J. 8, 17290–17307 (2021)
Samir, M., Sharafeddine, S., Assi, C.M., Nguyen, T.M., Ghrayeb, A.: UAV trajectory planning for data collection from time-constrained IoT devices. IEEE Trans. Wirel. Commun. 19(1), 34–46 (2020)
Wang, P., Yu, R., Gao, N., Lin, C., Liu, Y.: Task-driven data offloading for fog-enabled urban IoT services. IEEE Internet Things J. 8(9), 7562–7574 (2021)
Wu, Q., Liu, L., Zhang, R.: Fundamental trade-offs in communication and trajectory design for UAV-enabled wireless network. IEEE Wirel. Commun. 26(1), 36–44 (2019)
Xiang, C., et al.: Reusing delivery drones for urban crowdsensing. IEEE Trans. Mob. Comput. 1–17 (2022). (Early Access)
Xu, W., et al.: Minimizing the deployment cost of UAVs for delay-sensitive data collection in IoT networks. IEEE/ACM Trans. Netw. 30, 812–825 (2021)
Zhan, C., Zeng, Y.: Completion time minimization for multi-UAV-enabled data collection. IEEE Trans. Wirel. Commun. 18(10), 4859–4872 (2019)
Acknowledgments
This research is supported in part by the National Natural Science Foundation of China (62072320), the National Key R &D Program of China (2020YFB0704502), the Natural Science Foundation of Sichuan Province (2022NSFSC0569), the Key R &D Program of Sichuan Province (22ZDYF3599), and the Cooperative Program of Sichuan University and Yibin (2020CDYB-30).
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Xiang, Z., Liu, T., Peng, J. (2022). Weighted Data Loss Minimization in UAV Enabled Wireless Sensor Networks. In: Wang, L., Segal, M., Chen, J., Qiu, T. (eds) Wireless Algorithms, Systems, and Applications. WASA 2022. Lecture Notes in Computer Science, vol 13472. Springer, Cham. https://doi.org/10.1007/978-3-031-19214-2_10
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DOI: https://doi.org/10.1007/978-3-031-19214-2_10
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