Open Access iconOpen Access

ARTICLE

crossmark

Industrial Automation Information Analogy for Smart Grid Security

by Muhammad Asif1, Ishfaq Ali1, Shahbaz Ahmad1, Azeem Irshad2, Akber Abid Gardezi3, Fawaz Alassery4, Habib Hamam5, Muhammad Shafiq6,*

1 Department of Computer Science, National Textile University, Faisalabad, 37610, Punjab, Pakistan
2 Department of Computer Science and Software Engineering, International Islamic University, Islamabad, Pakistan
3 Department of Computer Science, COMSATS University Islamabad, Islamabad, Pakistan
4 Department of Computer Engineering, College of Computers and Information Technology, Taif University, Taif, Saudi Arabia
5 Faculty of Engineering, Moncton University, NB, E1A3E9, Canada
6 Department of Information and Communication Engineering, Yeungnam University, Gyeongsan, 38541, Korea

* Corresponding Author: Muhammad Shafiq. Email: email

Computers, Materials & Continua 2022, 71(2), 3985-3999. https://doi.org/10.32604/cmc.2022.023010

Abstract

Industrial automation or assembly automation is a strictly monitored environment, in which changes occur at a good speed. There are many types of entities in the focusing environment, and the data generated by these devices is huge. In addition, because the robustness is achieved by sensing redundant data, the data becomes larger. The data generating device, whether it is a sensing device or a physical device, streams the data to a higher-level deception device for calculation, so that it can be driven and configured according to the updated conditions. With the emergence of the Industry 4.0 concept that includes a variety of automation technologies, various data is generated through numerous devices. Therefore, the data generated for industrial automation requires unique Information Architecture (IA). IA should be able to satisfy hard real-time constraints to spontaneously change the environment and the instantaneous configuration of all participants. To understand its applicability, we used an example smart grid analogy. The smart grid system needs an IA to fulfill the communication requirements to report the hard real-time changes in the power immediately following the system. In addition, in a smart grid system, it needs to report changes on either side of the system, i.e., consumers and suppliers configure and reconfigure the system according to the changes. In this article, we propose an analogy of a physical phenomenon. A point charge is used as a data generating device, the streamline of electric flux is used as a data flow, and the charge distribution on a closed surface is used as a configuration. Finally, the intensity changes are used in the physical process, e.g., the smart grid. This analogy is explained by metaphors, and the structural mapping framework is used for its theoretical proof. The proposed analogy provides a theoretical basis for the development of such information architectures that can represent data flows, definition changes (deterministic and non-deterministic), events, and instantaneous configuration definitions of entities in the system. The proposed analogy provides a mechanism to perform calculations during communication, using a simple concept on the closed surface to integrate two-layer cyber-physical systems (computation, communication, and physical process). The proposed analogy is a good candidate for implementation in smart grid security.

Keywords


Cite This Article

APA Style
Asif, M., Ali, I., Ahmad, S., Irshad, A., Gardezi, A.A. et al. (2022). Industrial automation information analogy for smart grid security. Computers, Materials & Continua, 71(2), 3985-3999. https://doi.org/10.32604/cmc.2022.023010
Vancouver Style
Asif M, Ali I, Ahmad S, Irshad A, Gardezi AA, Alassery F, et al. Industrial automation information analogy for smart grid security. Comput Mater Contin. 2022;71(2):3985-3999 https://doi.org/10.32604/cmc.2022.023010
IEEE Style
M. Asif et al., “Industrial Automation Information Analogy for Smart Grid Security,” Comput. Mater. Contin., vol. 71, no. 2, pp. 3985-3999, 2022. https://doi.org/10.32604/cmc.2022.023010



cc Copyright © 2022 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 1601

    View

  • 1117

    Download

  • 0

    Like

Share Link