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Aerial Access Networks for Federated Learning: Applications and Challenges

Authors
Pham, Quoc-VietZeng, MingHuynh-The, ThienHan, ZhuHwang, Won-Joo
Issue Date
Jul-2022
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords
Multi-access edge computing; Collaborative work
Citation
IEEE NETWORK, v.36, no.3, pp 159 - 166
Pages
8
Journal Title
IEEE NETWORK
Volume
36
Number
3
Start Page
159
End Page
166
URI
https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/28382
DOI
10.1109/MNET.013.2100311
ISSN
0890-8044
1558-156X
Abstract
Aerial access networks (AANs) and mobile edge computing (MEC) have been considered as key enablers of future networks. In this article, we investigate the application of MEC-empowered AANs (also known as aerial computing) for federated learning (FL), a promising technology for providing private and distributed solutions to mobile edge networks. We first introduce the fundamentals of AANs and FL, and illustrate the potential benefits of aerial FL networks. On this basis, we present important applications of AANs for FL. It is shown that distinctive characteristics such as flexible deployment and high mobility, when exploited cleverly, can provide various benefits for FL-enabled networks. Finally, major challenges and potential directions are highlighted.
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