Data Collection Maximization for UAV-Enabled Wireless Sensor Networks

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Data collection in wireless sensor networks (WSNs) as a fundamental problem has been extensively studied in the past. With the fast deployment of 5G networks, the use of unmanned aerial vehicles (UAVs) for data collection in WSNs has become a promising technology due to its high flexibility, low cost and ease of deployment. Most existing studies of using UAVs for data collection focused on the one-to-one data collection scheme, where a UAV can collect the sensing data from one sensor at each time. There is another one-to-many data collection scheme where the UAV can collect sensing data from multiple sensors simultaneously through the Orthogonal Frequency Division Multiple Access technique. In this paper, we study data collection in WSNs by adopting the one-to-many data collection scheme with the aim to maximize the volume of data collected, subject to the energy capacity on the UAV. Specifically, we first formulate a novel multi-sensor data collection optimization problem and show that the problem is NP-hard. We then devise a $\left( {1 - \frac{1}{e}} \right)$-approximation algorithm for the problem. We finally evaluate the performance of the proposed algorithm through experimental simulations. Simulation results demonstrate that the proposed algorithm is promising, and outperforms other heuristics significantly.