  In this paper, we focus on energy-efficient UAV-based IoT data collection in
sensor networks in which the sensed data have different time deadlines. In the
investigated setting, the sensors are clustered and managed by cluster heads
(CHs), and multiple UAVs are used to collect data from the CHs. The formulated
problem is solved through a two-step approach. In the first step, an efficient
method is proposed to determine the minimal number of CHs and their best
locations. Subsequently, the minimal number of UAVs and their trajectories are
obtained by solving the associated capacitated vehicle routing problem. Results
show the efficiency of our proposed CHs placement method compared to baseline
approaches, where bringing the CHs closer to the dockstation allows significant
energy savings. Moreover, among different UAV trajectory planning algorithms,
Tabu search achieves the best energy consumption. Finally, the impact of the
battery capacity and time deadline are investigated in terms of consumed
energy, number of visited CHs, and number of deployed UAVs.
