Energy-efficient and Dynamic Consolidation of Virtual Machines in OpenStack-based Private Cloud

Abstract

Abstract Dynamic Virtual Machines (VMs) consolidation is an efficient technique for enhancing resource utilization and reducing energy consumption by the physical servers. Over-utilized host affects the degradation of resource utilization and VM performance. Determining when it is best to migrate VMs from an over-utilized host to an under-utilized host is the aim of dynamic Live VM Migration (LVM). It influences the resource utilization and Quality of Services (QoS) offered by cloud providers. In the OpenStack cloud, LVM is done manually, and it uses first-fit as a default migration technique, which is not efficient for resource utilization. The paper proposes a novel approach for the dynamic consolidation of VMs in the OpenStack cloud. The CPU utilization, RAM utilization, and the number of instances of each host are monitored over a period of time, and overload detection of a host is carried out using the SVM classification model. The Load balancing consolidation is performed based on the SVM classification result. Further, an energy-efficient consolidation achieved to optimize the energy of physical servers. We carry out the performance analysis of the proposed work in the OpenStack-based real-time testbed of five-node. The result reveals the fair distribution of load within the servers and the significant benefits of energy-efficient VM consolidation resulting up to 15% energy savings.