Energy efficiency is one of the main challenges that datacenters 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 datacenter 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 implemented our proposed energy management policy in Haizea as a real scheduling platform for virtualized datacenters. 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.
Source: University of Melbourne
Authors: Mohsen Amini Salehi | P. Radha Krishna | Krishnamurty Sai Deepak | Rajkumar Buyya