Abstract
Unmanned Aerial Vehicles (UAVs) are expected to be an important component in the upcoming wireless communication field, which are increasingly used as data collectors to gather sensing data from Wireless Sensor Networks (WSNs) due to their high mobility. Since the storage capacity and lifetime of sensors are increasing with the development of science and technology, sensors can store more and more sensing data about the monitoring area. However, due to the energy limitation of UAVs, we can not collect all data from WSN in limited time. Therefore, in this paper, we investigate the Maximizing Data Collection Proportion (MDCP) problem: given the limited budget of UAV, the objective is to find the trajectory of UAV such that the minimum data collection proportion of collected data to the stored data among all sensors is maximized. We first prove that the MDCP problem is NP-hard. Then we propose two approximation algorithms to design the trajectory of UAV, and give the theoretical analysis for the algorithms. Finally, we present numerical results in different scenarios to evaluate the effectiveness of the proposed algorithms.
This work was supported in part by the National Natural Science Foundation of China under Grants (11671400, 61672524).
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Luo, C., Wu, L., Chen, W., Wang, Y., Li, D., Wu, W. (2019). Trajectory Optimization of UAV for Efficient Data Collection from Wireless Sensor Networks. In: Du, DZ., Li, L., Sun, X., Zhang, J. (eds) Algorithmic Aspects in Information and Management. AAIM 2019. Lecture Notes in Computer Science(), vol 11640. Springer, Cham. https://doi.org/10.1007/978-3-030-27195-4_21
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DOI: https://doi.org/10.1007/978-3-030-27195-4_21
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