IoE based private multi-data center cloud architecture framework. (May 2022)

• Record Type: Journal Article
• Authors: Dhaya, R; Kanthavel, R
• Is Part Of: Computers & electrical engineering. Volume 100(2022)
• Publication Date: 2022-05
• Subjects: Multi-data centre management -- Private cloud -- Migration -- Security -- Automation -- Facility overhead; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2022.107933
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: An ensured cloud storage service over client's virtual machine processing services is guaranteed. Virtual machines and subsystems are even more powerful and useful by the proposals. Mitigation of private cloud computing systems resources is done. Improvement of Aggregated Migration Energy Consumption is obvious. Abstract: This paper proposes an Internet of Everything (IoE) based private multi-data center cloud architecture framework to utilize the merits of multi-data centers. The inclusive security structure for the entire cloud data center presented here is to minimize the potential vulnerabilities from the adoption of the cloud. This work would leverage the novelty in allocating the distribution of data smartly and in a reliable manner to have the network for private cloud data centers. On the other hand, the architecture must have the ability to make out an enterprise's data and association applications in the cloud using the facility of contributing the opportunity. To overcome these shortcomings, a "Facility Overhead-aware multi-objective Dynamic Private Cloud Data Center Algorithm" (FOMDPC) is proposed with the merits of migration payload awareness, dynamic load balancing methodology, and facility infrastructure costs. The factors to be considered to determine the efficiency are time complexity and memory overhead. In addition, aggregated migration energy consumption and aggregated SLA violations are also taken into account. Graphical abstract: Image, graphical abstract