DVFS-­aware consolidation for energy-efficient clouds

Resumen

Nowadays, data centers consume about 2\% of the worldwide energy production, originating more than 43 million tons of {CO2} per year. Cloud providers need to implement an energy-efficient management of physical resources in order to meet the growing demand for their services and ensure minimal costs. From the application-framework viewpoint, Cloud workloads present additional restrictions as 24/7 availability, and {SLA} constraints among others. Also, workload variation impacts on the performance of two of the main strategies for energy-efficiency in Cloud data centers: Dynamic Voltage and Frequency Scaling ({DVFS}) and Consolidation. Our work proposes two contributions: 1) a {DVFS} policy that takes into account the trade-offs between energy consumption and performance degradation; 2) a novel consolidation algorithm that is aware of the frequency that would be necessary when allocating a Cloud workload in order to maintain {QoS}. Our results demonstrate that including {DVFS} awareness in workload management provides substantial energy savings of up to 39.14\% for scenarios under dynamic workload conditions.