Manikandan S, Elakiya E, Rajheshwari K C, Sivakumar K
Department of Information Technology, E.G.S. Pillay Engineering College, Nagapattinam, Tamil Nadu, India.
School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India.
Sci Rep. 2024 Oct 2;14(1):22869. doi: 10.1038/s41598-024-72459-z.
Virtualization is the process of sharing physical machine resources into multiple Virtual Machines (VMs) for the effective utilization of resources. The major issues are in handling physical resources such as high demand of resources, infrastructure issues and operational issues. Also violating Service Level Agreement (SLA) is another problem to lead the violations. In this case, VM consolidation method is used to migrate the VMs and optimize the efficient way to use the resources. So we get minimized energy consumptions. Existing methods has increased energy consumption and overhead issues. In this paper we propose adaptive backtracking methods to provide VM consolidation based on less energy consumptions. We use Adaptive Hill Climbing and Pursuit algorithms to consolidate the VMs and use the VMs with efficient energy consumption. We implement this simulations using Matlab in Hybrid Cloud Environment. The performance factors are obtained with less energy consumption and compare the results with existing methods. Overall our proposed system is achieving 95% of accuracy index with lower energy consumption such as 28%, 30% and 32% with multiple VMs consolidations.
虚拟化是将物理机资源共享到多个虚拟机(VM)中以有效利用资源的过程。主要问题在于处理物理资源,如资源的高需求、基础设施问题和运营问题。此外,违反服务水平协议(SLA)是导致违规的另一个问题。在这种情况下,使用虚拟机整合方法来迁移虚拟机并优化资源使用的有效方式。这样我们就能将能源消耗降至最低。现有方法存在能源消耗增加和开销问题。在本文中,我们提出基于较少能源消耗的自适应回溯方法来进行虚拟机整合。我们使用自适应爬山算法和追踪算法来整合虚拟机,并使用能源消耗高效的虚拟机。我们在混合云环境中使用Matlab实现此模拟。在能源消耗较少的情况下获得性能因素,并将结果与现有方法进行比较。总体而言,我们提出的系统在多个虚拟机整合时,以28%、30%和32%等较低的能源消耗实现了95%的准确率指标。