Robust Edge Computing in UAV Systems via Scalable Computing and
Cooperative Computing
Abstract
Unmanned aerial vehicle (UAV) systems are of increasing interest to
academia and industry due to their mobility, flexibility and
maneuverability, and are an effective alternative to various uses such
as surveillance and mobile edge computing (MEC). However, due to their
limited computational and communications resources, it is difficult to
serve all computation tasks simultaneously. This article tackles this
problem by first proposing a scalable aerial computing solution, which
is applicable for computation tasks of multiple quality levels,
corresponding to different computation workloads and computation results
of distinct performances. It opens up the possibility to maximally
improve the overall computing performance with limited computational and
communications resources. To meet the demands for timely video analysis
that exceed the computing power of a UAV, we propose an aerial video
streaming enabled cooperative computing solution namely, UAVideo, which
streams videos from a UAV to ground servers. As a complement to scalable
aerial computing, UAVideo minimizes the video streaming time under the
constraints on UAV trajectory, video features, and communications
resources. Simulation results reveal the substantial advantages of the
proposed solutions. Besides, we highlight relevant directions for future
research.