i-manager Publications

Proposing a Matrix Model in Fog Computing for Expanding the Efficiency of Computing Frameworks

Shahazad Niwazi Qurashi*, Awakash Mishra**, Farrukh Sobia***, Ajeet Singh****, Mohd Faisal*****

* Department of Health Informatics, College of Public Health & Tropical Medicine, Jazan University, Saudi Arabia.

** School of Data Science, Maharishi University of Information Technology, Noida, India.

*** Department of Health Education and Promotion, College of Public Health & Tropical Medicine, Jazan University, Saudi Arabia.

**** School of Computer Science & Engineering, Galgotias University, Greater Noida, India.

***** Department of Computer Science, College of Engineering & Technology, Samara University, Afar, Ethiopia.

Periodicity:July - December'2022
DOI : https://doi.org/10.26634/jcc.9.2.19178

Abstract

Fog computing systems, by design, have a high degree of redundancy in terms of computing and storage resources. To make the most of this redundancy, coding techniques can be used to transform the data being transferred and processed. Two specific coding ideas that have been proposed for use in fog computing are minimum bandwidth codes and minimum latency codes. These codes have the potential to significantly reduce data transfer capacity utilization and computation inactivity. Minimum bandwidth codes focus on reducing the amount of data that needs to be transferred, while minimum latency codes focus on reducing the amount of time it takes for data to be processed. These two coding methods can be combined in a linked coding structure that allows for a trade-off between computation inactivity and communication load, leading to improved system performance. Fog computing has been proposed as a solution to meet the management requirements of the growing Internet of Things (IoT) and smart networks. This research breaks down the capabilities and challenges of fog computing in smart networks, presents the state-of-theart in the field, defines a fog computing-based smart grid, and provides a use case scenario for the proposed model.

Keywords

Fog Computing, Matrix Model, Framework, Smart Grid.

How to Cite this Article?

Qurashi, S. N., Mishra, A., Sobia, F., Singh, A, and Faisal, M. (2022). Proposing a Matrix Model in Fog Computing for Expanding the Efficiency of Computing Frameworks. i-manager’s Journal on Cloud Computing, 9(2), 1-12. https://doi.org/10.26634/jcc.9.2.19178

References

[1]. Backer, D. (2007). Power quality and asset management the other" two-thirds" of AMI value. In 2007 IEEE Rural Electric Power Conference (pp. C6-C6). IEEE. https://doi.org/10.1109/REPCON.2007.369560

[2]. Birman, K. P., Ganesh, L., & Van Renesse, R. (2011). Running smart grid control software on cloud computing architectures. In Workshop Computational Needs for the Next Generation Electric Grid. Cornell University (pp. 1-28).

[3]. Bitzer, B., & Gebretsadik, E. S. (2013). Cloud computing framework for smart grid applications. In 2013 48th International Universities' Power Engineering Conference (UPEC) (pp. 1-5). IEEE. https://doi.org/10.1109/UPEC.2013.6714855

[4]. Byun, J., Kim, Y., Hwang, Z., & Park, S. (2012). An intelligent cloud-based energy management system using machine to machine communications in future energy environments. In 2012 IEEE International Conference on Consumer Electronics (ICCE) (pp. 664-665). IEEE. https://doi.org/10.1109/ICCE.2012.6162018

[5]. Fang, X., Misra, S., Xue, G., & Yang, D. (2012). The new and improved power grid: a survey. IEEE Communications Surveys & Tutorials, 1-39. https://doi.org/10.1109/SURV.2011.101911.00087

[6]. Farhangi, H. (2009). The path of the smart grid. IEEE Power and Energy Magazine, 8(1), 18-28. https://doi.org/10.1109/MPE.2009.934876.

[7]. Gungor, V. C., Sahin, D., Kocak, T., Ergut, S., Buccella, C., Cecati, C., & Hancke, G. P. (2011). Smart grid technologies: Communication technologies and standards. IEEE Transactions on Industrial Informatics, 7(4), 529-539. https://doi.org/10.1109/TII.2011.2166794

[8]. Jin, X., He, Z., & Liu, Z. (2011). Multi-agent-based cloud architecture of smart grid. Energy Procedia, 12, 60-66. https://doi.org/10.1016/j.egypro.2011.10.010

[9]. Kursawe, K., Danezis, G., & Kohlweiss, M. (2011). Privacy-friendly aggregation for the smart-grid. In International Symposium on Privacy Enhancing Technologies Symposium (pp. 175-191). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22263-4_10

[10]. Long, X., Tipper, D., & Qian, Y. (2013). An advanced key management scheme for secure smart grid communications. In 2013 IEEE International Conference on Smart Grid Communications (SmartGridComm) (pp. 504-509). IEEE. https://doi.org/10.1109/SmartGridComm.2013.6688008

[11]. McKenna, E., Richardson, I., & Thomson, M. (2012). Smart meter data: Balancing consumer privacy concerns with legitimate applications. Energy Policy, 41, 807-814. https://doi.org/10.1016/j.enpol.2011.11.049

[12]. Mohsenian-Rad, A. H., & Leon-Garcia, A. (2010). Coordination of cloud computing and smart power grids. In 2010 First IEEE International Conference on Smart Grid Communications (pp. 368-372). IEEE. https://doi.org/10.1109/SMARTGRID.2010.5622069

[13]. Wang, W., Xu, Y., & Khanna, M. (2011). A survey on the communication architectures in smart grid. Computer Networks, 55(15), 3604-3629. https://doi.org/10.1016/j.comnet.2011.07.010

[14]. Yigit, M., Gungor, V. C., & Baktir, S. (2014). Cloud computing for smart grid applications. Computer Networks, 70, 312-329. https://doi.org/10.1016/j.comnet.2014.06.007

[15]. Yu, R., Zhang, Y., Gjessing, S., Yuen, C., Xie, S., & Guizani, M. (2011). Cognitive radio based hierarchical communications infrastructure for smart grid. IEEE Network, 25(5), 6-14. https://doi.org/10.1109/MNET.2011.6033030

	North Americas,UK, Middle East,Europe		India	Rest of world
	USD	EUR	INR	USD-ROW
Pdf	35	35	200	20
Online	35	35	200	15
Pdf & Online	35	35	400	25

Proposing a Matrix Model in Fog Computing for Expanding the Efficiency of Computing Frameworks

Abstract

Keywords

How to Cite this Article?

References

If you have access to this article please login to view the article or kindly login to purchase the article

Purchase Instant Access

Options for accessing this content: