In this chapter, we revisit the key concepts derived from each chapter in the book. Then, we discuss the future research directions and open issues to solve toward deploying Federated Learning at scale.

Wei Yang Bryan Lim; Jer Shyuan Ng; Zehui Xiong; Dusit Niyato; Chunyan Miao

doi:10.1007/978-3-031-07838-5_5

In this chapter, we revisit the key concepts derived from each chapter in the book. Then, we discuss the future research directions and open issues to solve toward deploying Federated Learning at scale.

Wei Yang Bryan Lim^*
, Jer Shyuan Ng
, Zehui Xiong
, Dusit Niyato
, Chunyan Miao

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

In this chapter, we revisit the key concepts derived from each chapter in the book. Then, we discuss the future research directions and open issues to solve toward deploying Federated Learning at scale.

Original language	English
Title of host publication	Federated learning over wireless edge networks
Publisher	Springer Nature
Pages	147-150
Number of pages	4
ISBN (Electronic)	9783031078385
ISBN (Print)	9783031078378, 9783031078408
DOIs	https://doi.org/10.1007/978-3-031-07838-5_5
Publication status	Published - 28 Sept 2022
Externally published	Yes

Publication series

Name	Wireless Networks (United Kingdom)
ISSN (Print)	2366-1186
ISSN (Electronic)	2366-1445

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

Communication efficiency
Edge intelligence
Federated learning
Incentive mechanism
Resource allocation

ASJC Scopus subject areas

Signal Processing
Information Systems
Computer Networks and Communications
Electrical and Electronic Engineering

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10.1007/978-3-031-07838-5_5Licence: Unspecified

Cite this

Lim, W. Y. B., Ng, J. S., Xiong, Z., Niyato, D., & Miao, C. (2022). In this chapter, we revisit the key concepts derived from each chapter in the book. Then, we discuss the future research directions and open issues to solve toward deploying Federated Learning at scale. In Federated learning over wireless edge networks (pp. 147-150). (Wireless Networks (United Kingdom)). Springer Nature. https://doi.org/10.1007/978-3-031-07838-5_5

Lim, Wei Yang Bryan ; Ng, Jer Shyuan ; Xiong, Zehui et al. / In this chapter, we revisit the key concepts derived from each chapter in the book. Then, we discuss the future research directions and open issues to solve toward deploying Federated Learning at scale. Federated learning over wireless edge networks. Springer Nature, 2022. pp. 147-150 (Wireless Networks (United Kingdom)).

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abstract = "In this chapter, we revisit the key concepts derived from each chapter in the book. Then, we discuss the future research directions and open issues to solve toward deploying Federated Learning at scale.",

keywords = "Communication efficiency, Edge intelligence, Federated learning, Incentive mechanism, Resource allocation",

author = "Lim, \{Wei Yang Bryan\} and Ng, \{Jer Shyuan\} and Zehui Xiong and Dusit Niyato and Chunyan Miao",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.",

year = "2022",

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Lim, WYB, Ng, JS, Xiong, Z, Niyato, D & Miao, C 2022, In this chapter, we revisit the key concepts derived from each chapter in the book. Then, we discuss the future research directions and open issues to solve toward deploying Federated Learning at scale. in Federated learning over wireless edge networks. Wireless Networks (United Kingdom), Springer Nature, pp. 147-150. https://doi.org/10.1007/978-3-031-07838-5_5

In this chapter, we revisit the key concepts derived from each chapter in the book. Then, we discuss the future research directions and open issues to solve toward deploying Federated Learning at scale. / Lim, Wei Yang Bryan; Ng, Jer Shyuan; Xiong, Zehui et al.
Federated learning over wireless edge networks. Springer Nature, 2022. p. 147-150 (Wireless Networks (United Kingdom)).

Research output: Chapter in Book/Report/Conference proceeding › Chapter

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Lim WYB, Ng JS, Xiong Z, Niyato D, Miao C. In this chapter, we revisit the key concepts derived from each chapter in the book. Then, we discuss the future research directions and open issues to solve toward deploying Federated Learning at scale. In Federated learning over wireless edge networks. Springer Nature. 2022. p. 147-150. (Wireless Networks (United Kingdom)). doi: 10.1007/978-3-031-07838-5_5

In this chapter, we revisit the key concepts derived from each chapter in the book. Then, we discuss the future research directions and open issues to solve toward deploying Federated Learning at scale.

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this