Energy Efficient and VM Consolidation Framework using Improved Spider Monkey Optimization Algorithm
Kethavath Prem Kumar1, Thirumalaisamy Ragunathan2, Devara Vasumathi3
1Kethavath Prem Kumar*, Research Scholar, ACE Engineering College, Department of Computer Science & Engineering, Hyderabad, India.
2Thirumalaisamy Ragunathan, Ph.D, SRM University, Department of Computer Science & Engineering, Amaravathi, India.
3Devara Vasumathi, Ph.D, Jawaharlal Nehru Technological University, Department of Computer Science & Engineering, Hyderabad, India.
Manuscript received on August 20, 2021. | Revised Manuscript received on August 26, 2021. | Manuscript published on September 30, 2021. | PP: 21-26 | Volume-10, Issue-3, September 2021. | Retrieval Number: 100.1/ijrte.C63900910321 DOI: 10.35940/ijrte.C6390.0910321
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Cloud Computing is rapidly being utilized to operate informational technological services by outstanding technologies for a variety of benefits, including dynamically improved resources planning and a new service delivery method. The Cloud computing process is occurred by allowing the client devices for data access through the internet from a remote server, computers, and the databases. An internet connection is linked among the front end users such as client device, network, browser, and software application with the back end that constitutes of servers, computers, and database. For satisfying the demands of the Service Level Agreement (SLA), providers of cloud service should reduce the usage of energy. Capacity reservations oriented system is available by clouds’ providers to permit users for customizing Virtual Machines (VMs) having specified age and geographic resources, reduces the amount to be paid for cloud services. To overcome the aforementioned issue, an Improved Spider Monkey Optimization (ISMO) approach is proposed for cloud center optimization. The VM consolidation architecture based on the proposed ISMO algorithm decreases energy usage while attempting to prevent Service Level Agreement breaches. The accessibility of hosts or virtual machines (VMs) for task performance is measured by fitness. If the number of tasks to be handled increases the hosts of VMs available at right state. The proposed VM consolidation architecture decreases energy usage while also attempting to prevent Service Level Agreement breaches and also provide energy-efficient computing in data centers. The proposed approach may be utilized to provide energy-efficient computing in data centers. The energy efficiency of the proposed ISMO method is achieved 28266 whereas, the existing algorithm showed an energy efficiency of 6009 and 10001.
Keywords: Cloud Computing, Information Technology, Service Level Agreement, Improved Spider Monkey Optimization, VM consolidation.