Article (Scientific journals)
FedFog: Network-Aware Optimization of Federated Learning over Wireless Fog-Cloud System
NGUYEN, van Dinh; CHATZINOTAS, Symeon; OTTERSTEN, Björn et al.
2022In IEEE Transactions on Wireless Communications, 21 (10)
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Keywords :
Distributed learning; edge intelligence; federated learning
Abstract :
[en] Federated learning (FL) is capable of performing large distributed machine learning tasks across multiple edge users by periodically aggregating trained local parameters. To address key challenges of enabling FL over a wireless fogcloud system (e.g., non-i.i.d. data, users’ heterogeneity), we first propose an efficient FL algorithm based on Federated Averaging (called FedFog) to perform the local aggregation of gradient parameters at fog servers and global training update at the cloud. Next, we employ FedFog in wireless fog-cloud systems by investigating a novel network-aware FL optimization problem that strikes the balance between the global loss and completion time. An iterative algorithm is then developed to obtain a precise measurement of the system performance, which helps design an efficient stopping criteria to output an appropriate number of global rounds. To mitigate the straggler effect, we propose a flexible user aggregation strategy that trains fast users first to obtain a certain level of accuracy before allowing slow users to join the global training updates. Extensive numerical results using several real-world FL tasks are provided to verify the theoretical convergence of FedFog. We also show that the proposed co-design of FL and communication is essential to substantially improve resource utilization while achieving comparable accuracy of the learning model.
Research center :
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > SIGCOM
Disciplines :
Electrical & electronics engineering
Author, co-author :
NGUYEN, van Dinh ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom
CHATZINOTAS, Symeon  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom
OTTERSTEN, Björn ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Duong, Trung Q.
External co-authors :
yes
Language :
English
Title :
FedFog: Network-Aware Optimization of Federated Learning over Wireless Fog-Cloud System
Publication date :
2022
Journal title :
IEEE Transactions on Wireless Communications
ISSN :
1536-1276
eISSN :
1558-2248
Publisher :
Institute of Electrical and Electronics Engineers, New York, United States - New York
Special issue title :
Machine Learning (cs.LG); Distributed, Parallel, and Cluster Computing (cs.DC)
Volume :
21
Issue :
10
Peer reviewed :
Peer Reviewed verified by ORBi
European Projects :
H2020 - 742648 - AGNOSTIC - Actively Enhanced Cognition based Framework for Design of Complex Systems
Funders :
H2020
CE - Commission Européenne [BE]
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since 11 April 2022

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