An Online Power Metering Model for Cloud Environment

Abstract

Energy consumption has become major operational cost in data centers. Virtualization technology used in cloud computing platforms can improve energy efficiency and reduce costs. There are many ongoing research projects focusing on power management for virtualized cloud by making power-aware resource allocation and scheduling policies. However, there is a lack of VM power profiling method in such research, because the power consumption of an individual virtual machine (VM) cannot be measured directly by hardware power meter. In this paper, a novel power metering model is proposed for VMs in the cloud environment, based on online monitoring of system resource metrics, to estimate the power consumption of a physical server as well as one or more VMs running on it. By analyzing problems found in experiments, the model is improved to be the classified-piecewise ternary linear regression model which can achieve higher accuracy. In addition, the model is proved to be effective by running a variety of sample programs. The implementation of our model shows that it can achieve average estimation accuracy of more than 96% with low runtime overhead.