Rough‐set and machine learning‐based approach for optimised virtual machine utilisation in cloud computing. Issue 6 (13th October 2020)

• Record Type: Journal Article
• Authors: Shylaja, B.S.; Bhaskar, R.
• Is Part Of: IET networks. Volume 9:Issue 6(2020)
• Page Start: 279
• Page End: 283
• Publication Date: 2020-10-13
• Subjects: computer centres -- cloud computing -- power aware computing -- learning (artificial intelligence) -- virtual machines -- rough set theory -- contracts; machine workload circumstances -- service level agreements -- machine learning‐based approach -- optimised virtual machine utilisation -- cloud computing -- computing resources -- information technology service providers -- cloud data centres -- virtual machine consolidation -- data centre energy consumption -- machine learning -- virtual machine selection -- selection strategy efficiency -- rough set -- migration control; Computer network architectures -- Periodicals; Computer network protocols -- Periodicals; Information networks -- Periodicals; Telecommunication systems -- Periodicals; 004.605
• DOI: 10.1049/iet-net.2020.0001
• Languages: English
• ISSNs: 2047-4954

Abstract

Abstract : To meet rising demands for computing resources, information technology service providers need to select cloud‐based services for their vitality and elasticity. Enormous numbers of data centres are designed to meet customer needs. Burning up energy by data centre is very high with the large‐scale deployment of cloud data centres. Virtual machine consolidation strategy implementation reduces the data centre energy consumption and guarantees service level agreements. This study proposes a machine learning‐based method in cloud computing for the automated use of virtual machines. Machine learning‐based virtual machine selection approach integrates the migration control mechanism that enhances selection strategy efficiency. The experiment is performed with various real machine workload circumstances to provide proof and effectiveness of the proposed method. The exploratory outcome shows that the proposed approach streamlines the utilisation of the virtual machine and diminishes the consumption of energy and improves infringement of service level agreements to accomplish better performance.