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A review of fog computing and machine learning: Concepts, applications, challenges, and open issues

Applications; Computer graphics; Decision making; Energy utilization; Fog; Green computing; Internet of things; Learning algorithms; Learning systems; Machine learning; Natural language processing systems; Speech recognition; Computing applications; Computing paradigm; Internet of Things (IOT); NAtu...

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Main Authors: Abdulkareem K.H., Mohammed M.A., Gunasekaran S.S., Al-Mhiqani M.N., Mutlag A.A., Mostafa S.A., Ali N.S., Ibrahim D.A.
Other Authors: 57197854295
Format: Review
Published: Institute of Electrical and Electronics Engineers Inc. 2023
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spelling my.uniten.dspace-249192023-05-29T15:28:50Z A review of fog computing and machine learning: Concepts, applications, challenges, and open issues Abdulkareem K.H. Mohammed M.A. Gunasekaran S.S. Al-Mhiqani M.N. Mutlag A.A. Mostafa S.A. Ali N.S. Ibrahim D.A. 57197854295 57192089894 55652730500 57197853907 57203180481 37036085800 56693765600 57191545030 Applications; Computer graphics; Decision making; Energy utilization; Fog; Green computing; Internet of things; Learning algorithms; Learning systems; Machine learning; Natural language processing systems; Speech recognition; Computing applications; Computing paradigm; Internet of Things (IOT); NAtural language processing; Neuromorphic computing; Research challenges; Research domains; Resource management; Fog computing Systems based on fog computing produce massive amounts of data; accordingly, an increasing number of fog computing apps and services are emerging. In addition, machine learning (ML), which is an essential area, has gained considerable progress in various research domains, including robotics, neuromorphic computing, computer graphics, natural language processing (NLP), decision-making, and speech recognition. Several researches have been proposed that study how to employ ML to settle fog computing problems. In recent years, an increasing trend has been observed in adopting ML to enhance fog computing applications and provide fog services, like efficient resource management, security, mitigating latency and energy consumption, and traffic modeling. Based on our understanding and knowledge, there is no study has yet investigated the role of ML in the fog computing paradigm. Accordingly, the current research shed light on presenting an overview of the ML functions in fog computing area. The ML application for fog computing become strong end-user and high layers services to gain profound analytics and more smart responses for needed tasks. We present a comprehensive review to underline the latest improvements in ML techniques that are associated with three aspects of fog computing: management of resource, accuracy, and security. The role of ML in edge computing is also highlighted. Moreover, other perspectives related to the ML domain, such as types of application support, technique, and dataset are provided. Lastly, research challenges and open issues are discussed. � 2013 IEEE. Final 2023-05-29T07:28:50Z 2023-05-29T07:28:50Z 2019 Review 10.1109/ACCESS.2019.2947542 2-s2.0-85074636899 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074636899&doi=10.1109%2fACCESS.2019.2947542&partnerID=40&md5=f6c93a8b97e9e87960d649efc7a14458 https://irepository.uniten.edu.my/handle/123456789/24919 7 8869895 153123 153140 All Open Access, Gold Institute of Electrical and Electronics Engineers Inc. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Applications; Computer graphics; Decision making; Energy utilization; Fog; Green computing; Internet of things; Learning algorithms; Learning systems; Machine learning; Natural language processing systems; Speech recognition; Computing applications; Computing paradigm; Internet of Things (IOT); NAtural language processing; Neuromorphic computing; Research challenges; Research domains; Resource management; Fog computing
author2 57197854295
author_facet 57197854295
Abdulkareem K.H.
Mohammed M.A.
Gunasekaran S.S.
Al-Mhiqani M.N.
Mutlag A.A.
Mostafa S.A.
Ali N.S.
Ibrahim D.A.
format Review
author Abdulkareem K.H.
Mohammed M.A.
Gunasekaran S.S.
Al-Mhiqani M.N.
Mutlag A.A.
Mostafa S.A.
Ali N.S.
Ibrahim D.A.
spellingShingle Abdulkareem K.H.
Mohammed M.A.
Gunasekaran S.S.
Al-Mhiqani M.N.
Mutlag A.A.
Mostafa S.A.
Ali N.S.
Ibrahim D.A.
A review of fog computing and machine learning: Concepts, applications, challenges, and open issues
author_sort Abdulkareem K.H.
title A review of fog computing and machine learning: Concepts, applications, challenges, and open issues
title_short A review of fog computing and machine learning: Concepts, applications, challenges, and open issues
title_full A review of fog computing and machine learning: Concepts, applications, challenges, and open issues
title_fullStr A review of fog computing and machine learning: Concepts, applications, challenges, and open issues
title_full_unstemmed A review of fog computing and machine learning: Concepts, applications, challenges, and open issues
title_sort review of fog computing and machine learning: concepts, applications, challenges, and open issues
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2023
_version_ 1806424419435806720
score 13.222552

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