Advancing the State of the Fog Computing to Enable 5G Network Technologies.

5G networks Fog computing IoT computing paradigm

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
21 Mar 2020
Historique:
received: 27 01 2020
revised: 12 03 2020
accepted: 18 03 2020
entrez: 5 4 2020
pubmed: 5 4 2020
medline: 5 4 2020
Statut: epublish

Résumé

Fog Computing (FC) is promising to Internet architecture for the emerging of modern technological approaches such as Fifth Generation (5G) networks and the Internet of Things (IoT). These are the advanced technologies that enable Internet architecture to enhance the data dissemination services based on numerous sensors generating continuous sensory information. It is tough for the current Internet architecture to meet up with the growing demands of the users for such a massive amount of information. Therefore, it needs to adopt modern technologies for efficient data dissemination services across the Internet. Thus, the FC and 5G are updating the data transmission using new technological approaches that are intelligently processing data to provide enhanced communications. This study proposes necessary measures to boost the growth of FC to 5G network usage. It is done by taking an extensive review of how 5G operates as well as studying its taxonomy, the idea of IoT, reviewed projects on IoT applicability, comparison of computing technologies, and the importance of FC. Moreover, it elaborates dynamic issues of computing network technologies, and information is provided on how to remedy these for future recommendations in the field of research and computing network technologies. This paper heavily focuses on the applications of FC as an enabler to the 5G network by identifying the necessary services and network-oriented features that are needed to be used in the place for an improved future enterprise network technology.

Identifiants

pubmed: 32245261
pii: s20061754
doi: 10.3390/s20061754
pmc: PMC7146597
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : National Research Foundation of Korea
ID : No. 2019R1A4A1023746, No. 2019R1F1A1060799

Références

Sensors (Basel). 2017 May 04;17(5):
pubmed: 28471390
J Diabetes Sci Technol. 2017 Jul;11(4):647-652
pubmed: 28745086
Entropy (Basel). 2017 Dec 23;20(1):
pubmed: 33265095

Auteurs

Yahui Meng (Y)

School of Science, Guangdong University of Petrochemical Technology, Maoming 525000, China.

Muhammad Ali Naeem (MA)

School of Science, Guangdong University of Petrochemical Technology, Maoming 525000, China.

Alaa Omran Almagrabi (AO)

Department of Information Systems, Faculty of Computing and Information Technology (FCIT), King Abdulaziz University, Jeddah 21589, Saudi Arabia.

Rashid Ali (R)

School of Intelligent Mechatronics Engineering, Sejong University, Seoul 05006, Korea.

Hyung Seok Kim (HS)

Department of Information and Communication Engineering, Sejong University, Seoul 05006, Korea.

Classifications MeSH