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

Author

Listed:
  • 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
    Computer Science Department, University of Quebec at Montreal (UQAM), Montreal, QC H2L 2C4, Canada)

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.

Suggested Citation

  • Elarbi Badidi & Zineb Mahrez & Essaid Sabir, 2020. "Fog Computing for Smart Cities’ Big Data Management and Analytics: A Review," Future Internet, MDPI, vol. 12(11), pages 1-28, October.
    • Handle: RePEc:gam:jftint:v:12:y:2020:i:11:p:190-:d:438300
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    Citations

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    Cited by:

    1. Mohammad Peyman & Pedro J. Copado & Rafael D. Tordecilla & Leandro do C. Martins & Fatos Xhafa & Angel A. Juan, 2021. "Edge Computing and IoT Analytics for Agile Optimization in Intelligent Transportation Systems," Energies, MDPI, vol. 14(19), pages 1-26, October.
    2. Halimjon Khujamatov & Khaleel Ahmad & Nargiza Usmanova & Jamshid Khoshimov & Mai Alduailij & Mona Alduailij, 2022. "Fog Computing Capabilities for Big Data Provisioning: Visualization Scenario," Sustainability, MDPI, vol. 14(13), pages 1-14, July.
    3. Karam M. Al-Obaidi & Mohataz Hossain & Nayef A. M. Alduais & Husam S. Al-Duais & Hossein Omrany & Amirhosein Ghaffarianhoseini, 2022. "A Review of Using IoT for Energy Efficient Buildings and Cities: A Built Environment Perspective," Energies, MDPI, vol. 15(16), pages 1-32, August.

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