Minimizing the number of deployed UAVs for delay-bounded data collection of IoT devices

In this paper, we study the deployment of Unmanned Aerial Vehicles (UAVs) to collect data from IoT devices, by finding the data collection tour of each UAV. To ensure the 'freshness' of the collected data, a strict requirement is that the total time spent in the tour of each UAV, which consists of UAV flying time and data collection time, must be no greater than a given maximum data collection delay B, e.g., 20 minutes. In this paper, we consider a problem of using the minimum number of UAVs and finding their data collection tours, subject to the constraint that the total time spent in each tour is no greater than B. We study two variants of the problem, one is that a UAV needs to fly to the location of each IoT device to collect its data; the other variant is that a UAV is able to collect the data of the IoT device as long as their Euclidean distance is no greater than a given wireless transmission range. For the first variant of the problem, we propose a novel 4-approximation algorithm, which improves the best approximation ratio $4\frac{4}{7}$ so far. For the second variant, we design the first constant factor approximation algorithm. In addition, we evaluate the performance of the proposed algorithms via extensive experiments, and experimental results show that the average numbers of UAVs deployed by the proposed algorithms are from 11% to 19% less than those by existing algorithms.