Preemption-Aware Energy Management in Virtualized Data Centers

Abstract

Energy efficiency is one of the main challenge hat data centers are facing nowadays. A considerable portion of the consumed energy in these environments is wasted because of idling resources. To avoid wastage, offering services with variety of SLAs (with different prices and priorities) is a common practice. The question we investigate in this research is how the energy consumption of a data center that offers various SLAs can be reduced. To answer this question we propose an adaptive energy management policy that employs virtual machine(VM) preemption to adjust the energy consumption based on user performance requirements. We have implementedour proposed energy management policy in Haize a as a real scheduling platform for virtualized data centers. Experimental results reveal 18% energy conservation (up to 4000 kWh in 30 days) comparing with other baseline policies without any major increase in SLA violation.