research-article

Robust Edge Computing in UAV Systems via Scalable Computing and Cooperative Computing

Authors:

Han HuAuthors Info & Claims

IEEE Wireless Communications, Volume 28, Issue 5

Pages 36 - 42

https://doi.org/10.1109/MWC.121.2100041

Published: 01 October 2021 Publication History

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. 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.

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Cited By

Yang LWang KXiao MZhang HLi MLi XJi H(2024)Online Data Driven Scheduling for Deadline-Sensitive Tasks of Mobile Edge Computing Enabled Consumer ElectronicsIEEE Transactions on Consumer Electronics10.1109/TCE.2024.336235070:1(4142-4154)Online publication date: 5-Feb-2024
https://dl.acm.org/doi/10.1109/TCE.2024.3362350
Zhang SLiu JShi ZWang JKato N(2023)Design and Optimization of RSMA for Coexisting HTC/MTC in 6G and Future NetworksIEEE Transactions on Wireless Communications10.1109/TWC.2023.327167322:12(9533-9548)Online publication date: 1-Dec-2023
https://dl.acm.org/doi/10.1109/TWC.2023.3271673
Mao ZHu FWu WWu HShen X(2023)Joint Distributed Beamforming and Backscattering for UAV-Assisted WPSNsIEEE Transactions on Wireless Communications10.1109/TWC.2022.320491522:3(1510-1522)Online publication date: 1-Mar-2023
https://dl.acm.org/doi/10.1109/TWC.2022.3204915
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cover image IEEE Wireless Communications

IEEE Wireless Communications Volume 28, Issue 5

October 2021

211 pages

ISSN:1536-1284

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IEEE Press

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Published: 01 October 2021

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Cited By

Yang LWang KXiao MZhang HLi MLi XJi H(2024)Online Data Driven Scheduling for Deadline-Sensitive Tasks of Mobile Edge Computing Enabled Consumer ElectronicsIEEE Transactions on Consumer Electronics10.1109/TCE.2024.336235070:1(4142-4154)Online publication date: 5-Feb-2024
https://dl.acm.org/doi/10.1109/TCE.2024.3362350
Zhang SLiu JShi ZWang JKato N(2023)Design and Optimization of RSMA for Coexisting HTC/MTC in 6G and Future NetworksIEEE Transactions on Wireless Communications10.1109/TWC.2023.327167322:12(9533-9548)Online publication date: 1-Dec-2023
https://dl.acm.org/doi/10.1109/TWC.2023.3271673
Mao ZHu FWu WWu HShen X(2023)Joint Distributed Beamforming and Backscattering for UAV-Assisted WPSNsIEEE Transactions on Wireless Communications10.1109/TWC.2022.320491522:3(1510-1522)Online publication date: 1-Mar-2023
https://dl.acm.org/doi/10.1109/TWC.2022.3204915
Li JDeng YSun WLi WLi RLi QLiu Z(2022)Resource Orchestration of Cloud-Edge–based Smart Grid Fault DetectionACM Transactions on Sensor Networks10.1145/352950918:3(1-26)Online publication date: 4-Apr-2022
https://dl.acm.org/doi/10.1145/3529509
Li QCheng HYang YTang HWang JLuo GSun W(2022)Deep Reinforcement Learning-based Resource Allocation for 5G Machine-type Communication in Active Distribution Networks with Time-varying InterferenceMobile Networks and Applications10.1007/s11036-022-02006-527:6(2264-2279)Online publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1007/s11036-022-02006-5

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