Title: Greedy-based task scheduling algorithm for minimising energy and power consumption for virtual machines in cloud environment
Authors: M.P. Abdul Razaak; Gufran Ahmad Ansari
Addresses: Department of Computer Application, B.S. Abdur Rahman Crescent Institute of Science and Technology, Chennai, Tamil Nadu, India ' Department of Computer Application, B.S. Abdur Rahman Crescent Institute of Science and Technology, Chennai, Tamil Nadu, India
Abstract: The research in cloud computing has the following significant elements, VMP referring to virtual machine placement and its energy efficiency. This paper proposes applying evolutionary computing in VMP which will result in active physical servers' reduction in numbers. This proposed method will also help in saving energy by scheduling under utilising servers. Task scheduling process is recommended in this article which minimises the energy consumed by active servers. Task scheduler is interlinked with cloud server with the help of VMP. Minimisation algorithm for active physical servers (MAPS) is an algorithm which has been used in this proposal in order to improve the efficiency. The active information that flows between the cloud server and VMP is controlled by MAPS algorithm. Java software is adopted to implement in this recommendation. The demonstrated experimental result shows that the proposed greedy algorithm performs better than existing state-of-arts in terms of energy efficiency.
Keywords: virtual machine placement; VMP; energy efficiency; cloud server; active servers; MAPS; task scheduling; greedy algorithm; evolutionary computing; cloud computing; active information; Java software.
International Journal of Cloud Computing, 2023 Vol.12 No.2/3/4, pp.424 - 434
Received: 16 Jul 2020
Accepted: 24 Feb 2021
Published online: 14 May 2023 *