Multilevel resource allocation for performance-aware energy-efficient cloud data centers

The massive power consumption of data centers has been a recurring concern in current research. In cloud environments, lots of methods are being adopted that aim for energy efficiency. However, although such methods enable the decrease in power consumption, they regularly affect application performance. In this paper, we present a multilevel resource allocation approach towards dynamic network bandwidth at the physical substrate, managing different power-saving states and workload allocation at the cloud infrastructure at the same time employ virtual machine allocation and selection policies at the cloud platform. In order to evaluate our approach, tests were carried out in a simulated environment using scale-out application on a dynamic cloud infrastructure. Results showed that our proposal presents a better balance regarding a more energy-efficient data center with a smaller impact on application performance when compared with other works discussed in the literature.