Version 1
: Received: 6 March 2019 / Approved: 7 March 2019 / Online: 7 March 2019 (12:44:18 CET)
How to cite:
Ramli, M.R.; Bhardwaj, S.; Kim, D. Toward Reliable Fog Computing Architecture for Industrial Internet of Things. Preprints2019, 2019030096. https://doi.org/10.20944/preprints201903.0096.v1
Ramli, M.R.; Bhardwaj, S.; Kim, D. Toward Reliable Fog Computing Architecture for Industrial Internet of Things. Preprints 2019, 2019030096. https://doi.org/10.20944/preprints201903.0096.v1
Ramli, M.R.; Bhardwaj, S.; Kim, D. Toward Reliable Fog Computing Architecture for Industrial Internet of Things. Preprints2019, 2019030096. https://doi.org/10.20944/preprints201903.0096.v1
APA Style
Ramli, M.R., Bhardwaj, S., & Kim, D. (2019). Toward Reliable Fog Computing Architecture for Industrial Internet of Things. Preprints. https://doi.org/10.20944/preprints201903.0096.v1
Chicago/Turabian Style
Ramli, M.R., Sanjay Bhardwaj and Dong-Seong Kim. 2019 "Toward Reliable Fog Computing Architecture for Industrial Internet of Things" Preprints. https://doi.org/10.20944/preprints201903.0096.v1
Abstract
Reliability is essential in industrial networks. In addition, most of the data from nodes of industrial Internet of Things (IIoT) are generated in real time. Thus, those data are mainly used for the time-sensitive applications. Furthermore, device failures should be considered when modeling reliable fog computing for IIoT. In this paper, we provide fundamental aspects to model reliable fog computing for IIoT. First, existing models of fog computing are compared. Then, the most feasible communication type to achieve a reliable system is determined from model analysis. Interaction modes are elaborated to study the advantages and drawbacks when communication is deployed in fog computing for IIoT, and challenges and solutions for reliable fog computing are discussed.
Keywords
IIoT; cloud computing; fog computing; reliability; architecture.
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
