Energy conservation in cloud infrastructures

With the growth of cloud computing, large scale data centers have become common in the computing industry, and there has been a significant increase in energy consumption at these data centers, which thus becomes a key issue to address. As most of the time a data center remains underutilized, a significant amount of energy can be conserved by migrating virtual machines (VM) running on underutilized machines to other machines and hibernating such underutilized machines. This paper aims to design such a strategy for energy-efficient cloud data centers. It makes use of historical traffic data from data centers and uses a service request prediction model which enables the identification of the number of active servers required at a given moment, thus making possible the hibernation of underutilized servers. The simulation results indicate that this approach brings about a significant amount of energy conservation.