  Having unmanned aerial vehicles (UAVs) with edge computing capability hover
over smart farmlands supports Internet of Things (IoT) devices with low
processing capacity and power to accomplish their deadline-sensitive tasks
efficiently and economically. In this work, we propose a graph neural
network-based reinforcement learning solution to optimize the task offloading
from these IoT devices to the UAVs. We conduct evaluations to show that our
approach reduces task deadline violations while also increasing the mission
time of the UAVs by optimizing their battery usage. Moreover, the proposed
solution has increased robustness to network topology changes and is able to
adapt to extreme cases, such as the failure of a UAV.
