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Review
. 2021 Dec 28;22(1):196.
doi: 10.3390/s22010196.

Recent Advances in Evolving Computing Paradigms: Cloud, Edge, and Fog Technologies

Nancy A Angel  1 , Dakshanamoorthy Ravindran  1 , P M Durai Raj Vincent  2 , Kathiravan Srinivasan  3 , Yuh-Chung Hu  4
Affiliations
Review

Recent Advances in Evolving Computing Paradigms: Cloud, Edge, and Fog Technologies

Nancy A Angel et al. Sensors (Basel). .

Abstract

Cloud computing has become integral lately due to the ever-expanding Internet-of-things (IoT) network. It still is and continues to be the best practice for implementing complex computational applications, emphasizing the massive processing of data. However, the cloud falls short due to the critical constraints of novel IoT applications generating vast data, which entails a swift response time with improved privacy. The newest drift is moving computational and storage resources to the edge of the network, involving a decentralized distributed architecture. The data processing and analytics perform at proximity to end-users, and overcome the bottleneck of cloud computing. The trend of deploying machine learning (ML) at the network edge to enhance computing applications and services has gained momentum lately, specifically to reduce latency and energy consumed while optimizing the security and management of resources. There is a need for rigorous research efforts oriented towards developing and implementing machine learning algorithms that deliver the best results in terms of speed, accuracy, storage, and security, with low power consumption. This extensive survey presented on the prominent computing paradigms in practice highlights the latest innovations resulting from the fusion between ML and the evolving computing paradigms and discusses the underlying open research challenges and future prospects.

Keywords: cloud computing; edge computing; fog computing; internet-of-things; machine learning.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

Figure 1
Figure 1
Organization of this survey paper.
Figure 2
Figure 2
PRISMA flow diagram for the selection process of the research articles used in this review.
Figure 3
Figure 3
Number and year of publications studied in this review.
Figure 4
Figure 4
Common cloud service models and their classifications.
Figure 5
Figure 5
Multi-access edge computing systems—a general architecture.
Figure 6
Figure 6
Mobile device–cloudlet–cloud model.
Figure 7
Figure 7
Fog computing and its related computing paradigms.
Figure 8
Figure 8
Typical cloud–fog computing architecture.
Figure 9
Figure 9
N-tier architecture.
Figure 10
Figure 10
Typical fog computing architectural layers.
Figure 11
Figure 11
Applications of fog computing.
Figure 12
Figure 12
Cloud, fog, and edge computing alliance.
Figure 13
Figure 13
Fog computing—open challenges.
Figure 14
Figure 14
Future opportunities—fog computing and other evolving computing paradigms.
See this image and copyright information in PMC

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