Dynamic Virtual Machine Consolidation Algorithm Based on Balancing Energy Consumption and Quality of Service

Abstract

Virtual machine consolidation (VMC) is an effective way to solve the problems of high power consumption and low utilization in cloud data centers. However, large-scale virtual machine migrations (VMMs) can result in additional workloads, service-level agreement violations (SLAVs), and considerable energy consumption (EC). Existing studies have made great progress in this respect, but the following problems remain: first, the potential overload of the physical host is not considered in the load detection of the physical host; second, the resource-demand scaling of physical hosts is not considered during virtual machine (VM) placement, which results in the lack of accuracy in selecting suitable hosts. In view of the above problems, this study firstly constructs a virtual resource consolidation model based on green energy conservation (GEC-VRCM), which defines the specific process and related attributes of VMC, which is beneficial to improve the consolidation efficiency of virtual resources. Second, based on this model, we propose a dynamic virtual machine consolidation algorithm based on balancing energy consumption and quality of service (EQ-DVMCA) to achieve efficient consolidation of virtual resources. Finally, experiments show that, compared with the selected 12 benchmark algorithms and two advanced VMC algorithms, EQ-DVMCA not only reduces the number of VMMs and EC, but also maintains a high level of Quality of Service (QoS) and achieves a balance between EC and QoS.