Virtual machine customization and task mapping architecture for efficient allocation of cloud data center resources

Abstract

Energy usage of large-scale data centers has become a major concern for cloud providers. There has been an active effort in techniques for the minimization of the energy consumed in the data centers. However, most approaches lack the analysis and application of real cloud backend traces. In existing approaches, the variation of cloud workloads and its effect on the performance of the solutions are not investigated. Furthermore, the focus of existing approaches is on virtual machine migration and placement algorithms, with little regard to tailoring virtualmachine configuration to workload characteristics, which can further reduce the energy consumption and resource wastage in a typical data ..