Optimised Secure Clustering and Energy Efficient System for IIoT Data in Cloud Environment

被引:0
作者
Primya, T. [1 ]
Yadav, Ajit Kumar Singh [2 ]
Sreeraman, Y. [3 ]
Vivekanandan, T. [3 ]
机构
[1] Department of Computer Science and Engineering, KPR Institute of Engineering and Technology, Tamilnadu, Coimbatore
[2] Department of Computer Science & Engineering, North Eastern Regional Institute of Science and Technology, Itanagar
[3] Department of Computer Science and Engineering, School of Technology, The Apollo University, Andhra Pradesh, Chittoor
关键词
Cloud Environment; Energy; Industrial Internet of Things; Security;
D O I
10.4108/EW.6032
中图分类号
学科分类号
摘要
Secure and robust Industrial Internet of Things (IIoT) statistics dealing with cloud infrastructures are vital as commercial gadgets become more networked. IIoT systems accommodated in the cloud should shield personal statistics, ensure uninterrupted operations, use information insights to make decisions and reduce electricity consumption. Several industries have been transformed through IIoT programs, which depend closely on cloud infrastructure for statistics processing and garages. Energy performance and the safety of sensitive business statistics are predominant issues. Some problems that need addressing are secure data transmission, invasion of privacy, and data breaches. It is not a simple task to optimise power efficiency without compromising actual-time records processing. The Optimised Dynamic Clustering and Energy-Efficient System (ODC-EES) is a unique approach for cloud-based IIoT information control and employers that uses stepped-forward adaptive clustering strategies. Strengthening facts security whilst streamlining strength use, the recommended method blends present-day encryption protocols, access controls, and power-aware helpful resource allocation. This method promotes sustainable electricity practices even by ensuring adaptability to the ever-converting IIoT information. Manufacturing, strength, logistics, and healthcare are a few commercial sectors that might benefit from the proposed method. The counselled approach seeks to enhance the dependability and performance of manufacturing strategies by making information more stable and using less strength. To demonstrate the system's efficacy in enhancing statistics protection, optimising energy usage, and ensuring the fresh operation of IIoT programs in cloud environments, these simulations will evaluate its overall performance in numerous situations. © 2024 T.Primya et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.
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