Title
Optimizing Federated Learning in Distributed Industrial IoT: A Multi-Agent Approach
Abstract
In this paper, we aim to make the best joint decision of device selection and computing and spectrum resource allocation for optimizing federated learning (FL) performance in distributed industrial Internet of Things (IIoT) networks. To implement efficient FL over geographically dispersed data, we introduce a three-layer collaborative FL architecture to support deep neural network (DNN) training. ...
Year
DOI
Venue
2021
10.1109/JSAC.2021.3118352
IEEE Journal on Selected Areas in Communications
Keywords
DocType
Volume
Servers,Resource management,Industrial Internet of Things,Computer architecture,Energy consumption,Computational modeling,Delays
Journal
39
Issue
ISSN
Citations 
12
0733-8716
8
PageRank 
References 
Authors
0.49
0
7
Name
Order
Citations
PageRank
Zhang Wei139253.03
Dong Yang2182.64
wen wu311715.85
Haixia Peng480.49
Ning Zhang574459.81
Hongke Zhang61637142.17
Xuemin Shen715389928.67