Vishwas Kumar Sharma, Pramod Kumar, Neetu Singh and Nishant Kumar Rathi

Department of Computer Application, Shri Ram College, Muzaffarnagar, UP. India

Received: Oct 24, 2021/ Revised: Nov 28, 2021/Accepted: Nov 30, 2021

Abstract

Nowadays, the Internet of Things (IoT) is an increasingly popular technology that generates a vast amount of data. By applying data analytics techniques to discrete data through Cloud Computing, valuable and precise information can be obtained. However, when it comes to traditional applications and IoT applications such as environmental monitoring, smart navigation, and smart healthcare, there are specific requirements to consider, including mobility, quick response, and real-time capabilities. Unfortunately, the conventional cloud computing architecture falls short in meeting these requirements due to the distributed processing of data across various physical locations of IIoT devices worldwide. Consequently, the concept of edge computing has emerged, enabling data storage and processing at the network’s extreme end, closer to the data collection sources than cloud storage. This approach enhances computational efficiency and location awareness in applications. Nevertheless, the integration of edge computing with IoT devices presents several security and privacy challenges in the realm of data analytics.

Keywords: Cloud computing, IOT, Edge Computing, Edge devices, IOT.

References

Altenhof, T. (2023). Towards Intelligent Repair : Observations on AI and Architecture. KWI Blog. https://doi.org/10.37189/kwi-blog/20230508-0830

Beri, R. (2015). Descriptive Study of Cloud Computing An Emerging Technology. International Journal on Recent and Innovation Trends in Computing and Communication, 3(3), 1401–1404. https://doi.org/10.17762/ijritcc2321-8169.1503108

Beri, R. (2015). Descriptive Study of Cloud Computing An Emerging Technology. International Journal on Recent and Innovation Trends in Computing and Communication, 3(3), 1401–1404. https://doi.org/10.17762/ijritcc2321-8169.1503108

Bilal, K., Malik, S. U. R., Khan, S. U., & Zomaya, A. Y. (2014). Trends and challenges in cloud datacenters. IEEE Cloud Computing, 1(1), 10–20. https://doi.org/10.1109/mcc.2014.26

Geiogtsucs Us Gaooebubg!: 78th Annual Meeting—A daily overview. (2008). The Leading Edge, 27(10), 1304–1304. https://doi.org/10.1190/tle27101304.1

Jabbar, I. (2016). Using Fully Homomorphic Encryption to Secure Cloud Computing. Internet of Things and Cloud Computing, 4(2), 13. https://doi.org/10.11648/j.iotcc.20160402.12

Pace, P., Aloi, G., Gravina, R., Caliciuri, G., Fortino, G., & Liotta, A. (2019). An Edge-Based Architecture to Support Efficient Applications for Healthcare Industry 4.0. IEEE Transactions on Industrial Informatics, 15(1), 481–489. https://doi.org/10.1109/tii.2018.2843169

Ren, J., He, Y., Huang, G., Yu, G., Cai, Y., & Zhang, Z. (2019). An Edge-Computing Based Architecture for Mobile Augmented Reality. IEEE Network, 33(4), 162–169. https://doi.org/10.1109/mnet.2018.1800132

Sanheji, M. (2015). Rejuvenation in Virtualized Servers. Communications, 3(5), 109. https://doi.org/10.11648/j.com.20150305.15

Singh, A. (2019). Edge Computing Architecture With an Extension. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3387144

How to cite this article

Sharma, V. K., Kumar, P., Singh, N. and Rathi, N. K. (2021). Edge computing: an evolution and paradigm shift in the realm of cloud computing and IOT. Science Archives, Vol. 2(4), 386-391. https://doi.org/10.47587/SA.2021.2420

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