Open Access
Open access
MDPI
Sensors
,  volume 23 ,  issue 17 ,  pages 7358

Limitations and Future Aspects of Communication Costs in Federated Learning: A Survey

Publication type: Journal Article
Publication date: 2023-08-23
MDPI
scimago Q1
wos Q2
SJR: 0.764
CiteScore: 8.2
Impact factor: 3.5
ISSN: 14243210, 14248220
DOI:  10.3390/s23177358
PubMed ID:  37687814
Biochemistry
Analytical Chemistry
Atomic and Molecular Physics, and Optics
Electrical and Electronic Engineering
Instrumentation
Abstract

This paper explores the potential for communication-efficient federated learning (FL) in modern distributed systems. FL is an emerging distributed machine learning technique that allows for the distributed training of a single machine learning model across multiple geographically distributed clients. This paper surveys the various approaches to communication-efficient FL, including model updates, compression techniques, resource management for the edge and cloud, and client selection. We also review the various optimization techniques associated with communication-efficient FL, such as compression schemes and structured updates. Finally, we highlight the current research challenges and discuss the potential future directions for communication-efficient FL.

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GOST |
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GOST Copy
Asad M. et al. Limitations and Future Aspects of Communication Costs in Federated Learning: A Survey // Sensors. 2023. Vol. 23. No. 17. p. 7358.
GOST all authors (up to 50) Copy
Asad M., Shaukat S., Hu D., WANG Z., Javanmardi E., Nakazato J., Tsukada M. Limitations and Future Aspects of Communication Costs in Federated Learning: A Survey // Sensors. 2023. Vol. 23. No. 17. p. 7358.
RIS |
Cite this
RIS Copy
TY - JOUR
DO - 10.3390/s23177358
UR - https://doi.org/10.3390/s23177358
TI - Limitations and Future Aspects of Communication Costs in Federated Learning: A Survey
T2 - Sensors
AU - Asad, Muhammad
AU - Shaukat, Saima
AU - Hu, Dou
AU - WANG, ZEKUN
AU - Javanmardi, Ehsan
AU - Nakazato, Jin
AU - Tsukada, Manabu
PY - 2023
DA - 2023/08/23
PB - MDPI
SP - 7358
IS - 17
VL - 23
PMID - 37687814
SN - 1424-3210
SN - 1424-8220
ER -
BibTex |
Cite this
BibTex (up to 50 authors) Copy
@article{2023_Asad,
author = {Muhammad Asad and Saima Shaukat and Dou Hu and ZEKUN WANG and Ehsan Javanmardi and Jin Nakazato and Manabu Tsukada},
title = {Limitations and Future Aspects of Communication Costs in Federated Learning: A Survey},
journal = {Sensors},
year = {2023},
volume = {23},
publisher = {MDPI},
month = {aug},
url = {https://doi.org/10.3390/s23177358},
number = {17},
pages = {7358},
doi = {10.3390/s23177358}
}
MLA
Cite this
MLA Copy
Asad, Muhammad, et al. “Limitations and Future Aspects of Communication Costs in Federated Learning: A Survey.” Sensors, vol. 23, no. 17, Aug. 2023, p. 7358. https://doi.org/10.3390/s23177358.