A prediction-based and power-aware virtual machine allocation algorithm in three-tier cloud data centers

With the increasing popularity of cloud computing services, the more number of cloud data centers are constructed over the globe. This makes the power consumption of cloud data center elements as a big challenge. Hereby, several software and hardware approaches have been proposed to handle this issue. However, this problem has not been optimally solved yet. In this paper, we propose an online cloud resource management with live migration of virtual machines (VMs) to reduce power consumption. To do so, a prediction-based and power-aware virtual machine allocation algorithm is proposed. Also, we present a three-tier framework for energy-efficient resource management in cloud data centers. Experimental results indicate that the proposed solution reduces the power consumption; at the same time, service-level agreement violation (SLAV) is also improved.