Dynamic Voltage and Frequency Scaling-aware dynamic consolidation of virtual machines for energy efficient cloud data centers

Computational demand in data centers is increasing because of the growing popularity of Cloud applications. However, data centers are becoming unsustainable in terms of power consumption and growing energy costs so Cloud providers have to face the major challenge of placing them on a more scalable curve. Also, Cloud services are provided under strict Service Level Agreement conditions, so trade-offs between energy and performance have to be taken into account. Techniques as Dynamic Voltage and Frequency Scaling (DVFS) and consolidation are commonly used to reduce the energy consumption in data centers, although they are applied independently and their effects on Quality of Service are not always considered. Thus, understanding the relationship between power, DVFS, consolidation, and performance is crucial to enable energy-efficient management at the data center level. In this work, we propose a DVFS policy that reduces power consumption while preventing performance degradation, and a DVFS-aware consolidation policy that optimizes consumption, considering the DVFS configuration that would be necessary when mapping Virtual Machines to maintain Quality of Service. We have performed an extensive evaluation on the CloudSim toolkit using real Cloud traces and an accurate power model based on data gathered from real servers. Our results demonstrate that including DVFS awareness in workload management provides substantial energy savings of up to 41.62% for scenarios under dynamic workload conditions. These outcomes outperforms previous approaches, that do not consider integrated use of DVFS and consolidation strategies.