TY - JOUR
T1 - Robust Edge Computing in UAV Systems via Scalable Computing and Cooperative Computing
AU - Liu, Zhi
AU - Zhan, Cheng
AU - Cui, Ying
AU - Wu, Celimuge
AU - Hu, Han
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/10/1
Y1 - 2021/10/1
N2 - 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. 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 performance. 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. Furthermore, we highlight relevant directions for future research.
AB - 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. 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 performance. 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. Furthermore, we highlight relevant directions for future research.
UR - http://www.scopus.com/inward/record.url?scp=85119973828&partnerID=8YFLogxK
U2 - 10.1109/MWC.121.2100041
DO - 10.1109/MWC.121.2100041
M3 - Article
AN - SCOPUS:85119973828
SN - 1536-1284
VL - 28
SP - 36
EP - 42
JO - IEEE Wireless Communications
JF - IEEE Wireless Communications
IS - 5
ER -