A Systematic Literature Review on Distributed Machine Learning in Edge Computing

Carlos Poncinelli Filho; Elias Marques; Victor Chang; Leonardo Dos Santos; Flavia Bernardini; Paulo F. Pires; Luiz Ochi; Flavia C. Delicato

doi:10.3390/s22072665

A Systematic Literature Review on Distributed Machine Learning in Edge Computing

Carlos Poncinelli Filho, Elias Marques, Victor Chang, Leonardo Dos Santos, Flavia Bernardini, Paulo F. Pires, Luiz Ochi, Flavia C. Delicato^*

^*Corresponding author for this work

Research output: Contribution to journal › Review article › peer-review

Abstract

Distributed edge intelligence is a disruptive research area that enables the execution of machine learning and deep learning (ML/DL) algorithms close to where data are generated. Since edge devices are more limited and heterogeneous than typical cloud devices, many hindrances have to be overcome to fully extract the potential benefits of such an approach (such as data-in-motion analytics). In this paper, we investigate the challenges of running ML/DL on edge devices in a distributed way, paying special attention to how techniques are adapted or designed to execute on these restricted devices. The techniques under discussion pervade the processes of caching, training, inference, and offloading on edge devices. We also explore the benefits and drawbacks of these strategies.

Original language	English
Article number	2665
Journal	Sensors
Volume	22
Issue number	7
DOIs	https://doi.org/10.3390/s22072665
Publication status	Published - 30 Mar 2022

Bibliographical note

© 2022 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).

Funding Information:
This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de
Nível Superior—Brasil (CAPES)—Finance Code 001, also by Brazilian funding agencies FAPESP
(grant number 2015/24144-7), FAPERJ and CNPq. Prof. Chang’s work is partly supported by VC
Research (VCR0000170).

Keywords

artificial intelligence
distributed
edge intelligence
fog intelligence
Internet of Things
machine learning

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10.3390/s22072665Licence: CC BY 4.0

A Systematic Literature Review on Distributed Machine Learning in Edge Computing
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).
Final published version, 847 KBLicence: CC BY 4.0

Cite this

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A Systematic Literature Review on Distributed Machine Learning in Edge Computing

Abstract

Bibliographical note

Keywords

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