Energy-credit scheduler: An energy-aware virtual machine scheduler for cloud systems

Abstract

Virtualization facilitates the provision of flexible resources and improves energy efficiency through the consolidation of virtualized servers into a smaller number of physical servers. As an increasingly essential component of the emerging cloud computing model, virtualized environments bill their users based on processor time or the number of virtual machine instances. However, accounting based only on the depreciation of server hardware is not sufficient because the cooling and energy costs for data centers will exceed the purchase costs for hardware. This paper suggests a model for estimating the energy consumption of each virtual machine without dedicated measurement hardware. Our model estimates the energy consumption of a virtual machine based on in-processor events generated by the virtual machine. Based on this estimation model, we also propose a virtual machine scheduling algorithm that can provide computing resources according to the energy budget of each virtual machine. The suggested schemes are implemented in the Xen virtualization system, and an evaluation shows that the suggested schemes estimate and provide energy consumption with errors of less than 5% of the total energy consumption.