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Cited by 1,022IoT and Edge/Fog ComputingCloud Computing and Resource ManagementSoftware-Defined Networks and 5G

A Comprehensive Survey on Fog Computing: State-of-the-Art and Research Challenges

Open access
Mouradian, Carla, Naboulsi, Diala, Yangui, Sami, Glitho, Roch H., Morrow, Monique J., Polakos, Paul A.·2018·IEEE Communications Surveys & Tutorials
DOI 10.1109/comst.2017.2771153
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Abstract

Cloud computing with its three key facets (i.e., Infrastructure-as-a-Service, Platform-as-a-Service, and Software-as-a-Service) and its inherent advantages (e.g., elasticity and scalability) still faces several challenges. The distance between the cloud and the end devices might be an issue for latency-sensitive applications such as disaster management and content delivery applications. Service level agreements (SLAs) may also impose processing at locations where the cloud provider does not have data centers. Fog computing is a novel paradigm to address such issues. It enables provisioning resources and services outside the cloud, at the edge of the network, closer to end devices, or eventually, at locations stipulated by SLAs. Fog computing is not a substitute for cloud computing but a powerful complement. It enables processing at the edge while still offering the possibility to interact with the cloud. This paper presents a comprehensive survey on fog computing. It critically reviews the state of the art in the light of a concise set of evaluation criteria. We cover both the architectures and the algorithms that make fog systems. Challenges and research directions are also introduced. In addition, the lessons learned are reviewed and the prospects are discussed in terms of the key role fog is likely to play in emerging technologies such as tactile Internet.

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  • Edge computing has become an important solution to break the bottleneck of emerging technologies by reducing data transmission, improving service latency and easing cloud computing pressure.

    “Edge computing has become an important solution to break the bottleneck of emerging technologies by virtue of its advantages of reducing data transmission, improving service latency and easing cloud computing pressure.”

    From Convergence of Edge Computing and Deep Learning: A Comprehensive Survey (2020) · cites this paper as [22]

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Authors
Mouradian, C., Naboulsi, D., Yangui, S., Glitho, R. H., Morrow, M. J., & Polakos, P. A.
Affiliations
  • Concordia University (CA)
  • Centre National de la Recherche Scientifique (FR)
  • Cisco Systems (United States) (US)
ORCID
Venue
IEEE Communications Surveys & Tutorials
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2018
Volume
20
Issue
1
Pages
416-464
ISSN
1553-877X (ISSN-L)
DOI
10.1109/comst.2017.2771153
OpenAlex
W2766722289
Cited by
1,022
References
6
Citations by year
2026: 47 · 2025: 64 · 2024: 76 · 2023: 118 · 2022: 145 · 2021: 151 · 2020: 180 · 2019: 153 · 2018: 86 · 2017: 2
FWCI
73.65
Type
journal article
Language
en
Open access
Licence
Locations
  • IEEE Communications Surveys & Tutorials (publishedVersion)
  • arXiv (Cornell University) (submittedVersion, public-domain)
  • Espace ÉTS (ETS) (submittedVersion)
  • UWC Research Repository (University of the Western Cape) (submittedVersion)
  • arXiv (Cornell University)
Funders
  • CISCO Systems (CG-589630)
  • Canadian National Sciences and Engineering Research Council through a Discovery Grant
Topics
  • Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
  • Physical Sciences › Computer Science › Information Systems › Cloud Computing and Resource Management
  • Physical Sciences › Computer Science › Computer Networks and Communications › Software-Defined Networks and 5G
Keywords
fog computing, edge computing, cloud computing, delay-sensitive applications, service level agreements, fog computing architecture, tactile internet, disaster management, content distribution

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