Filho, Carlos Poncinelli, Marques, Elias, Chang, Victor, Dos Santos, Leonardo, Bernardini, Flavia, Pires, Paulo F., Ochi, Luiz and Delicato, Flavia C. (2022). A Systematic Literature Review on Distributed Machine Learning in Edge Computing. Sensors, 22 (7),
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.
Publication DOI: | https://doi.org/10.3390/s22072665 |
---|---|
Divisions: | College of Business and Social Sciences > Aston Business School College of Business and Social Sciences > Aston Business School > Operations & Information Management |
Funding Information: | This study was financed in part by the Coordena??o de Aperfei?oamento de Pessoal de N?vel 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 suppor |
Additional Information: | © 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). |
Uncontrolled Keywords: | artificial intelligence,distributed,edge intelligence,fog intelligence,Internet of Things,machine learning,Analytical Chemistry,Information Systems,Atomic and Molecular Physics, and Optics,Biochemistry,Instrumentation,Electrical and Electronic Engineering |
Publication ISSN: | 1424-8220 |
Last Modified: | 03 Oct 2024 07:26 |
Date Deposited: | 25 May 2022 10:25 |
Full Text Link: | |
Related URLs: |
http://www.scop ... tnerID=8YFLogxK
(Scopus URL) https://www.mdp ... -8220/22/7/2665 (Publisher URL) |
PURE Output Type: | Review article |
Published Date: | 2022-03-30 |
Accepted Date: | 2022-03-23 |
Authors: |
Filho, Carlos Poncinelli
Marques, Elias Chang, Victor ( 0000-0002-8012-5852) Dos Santos, Leonardo Bernardini, Flavia Pires, Paulo F. Ochi, Luiz Delicato, Flavia C. |