Fog Computing for Smart Cities’ Big Data Management and Analytics: A Review

Elarbi Badidi, Zineb Mahrez and Essaid Sabir
Additional contact information
Elarbi Badidi: Department of Computer Science and Software Engineering, College of Information Technology, UAE University, AL-AIN P.O. Box. 15551, UAE
Zineb Mahrez: NEST Research Group, LRI. Lab, ENSEM, Hassan II University of Casablanca, Casablanca 9167, Morocco
Essaid Sabir: NEST Research Group, LRI. Lab, ENSEM, Hassan II University of Casablanca, Casablanca 9167, Morocco

Future Internet, 2020, vol. 12, issue 11, 1-28

Abstract: Demographic growth in urban areas means that modern cities face challenges in ensuring a steady supply of water and electricity, smart transport, livable space, better health services, and citizens’ safety. Advances in sensing, communication, and digital technologies promise to mitigate these challenges. Hence, many smart cities have taken a new step in moving away from internal information technology (IT) infrastructure to utility-supplied IT delivered over the Internet. The benefit of this move is to manage the vast amounts of data generated by the various city systems, including water and electricity systems, the waste management system, transportation system, public space management systems, health and education systems, and many more. Furthermore, many smart city applications are time-sensitive and need to quickly analyze data to react promptly to the various events occurring in a city. The new and emerging paradigms of edge and fog computing promise to address big data storage and analysis in the field of smart cities. Here, we review existing service delivery models in smart cities and present our perspective on adopting these two emerging paradigms. We specifically describe the design of a fog-based data pipeline to address the issues of latency and network bandwidth required by time-sensitive smart city applications.

Keywords: fog computing; cloud computing; smart cities; smart grids; smart transportation; smart healthcare; big data; data storage; data analytics; data pipeline; data processing (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.mdpi.com/1999-5903/12/11/190/pdf (application/pdf)
https://www.mdpi.com/1999-5903/12/11/190/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jftint:v:12:y:2020:i:11:p:190-:d:438300

Access Statistics for this article

Future Internet is currently edited by Ms. Grace You

More articles in Future Internet from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().