A Power and Performance Management Framework for Virtualized Server Clusters

Nowadays, one of the most important goals of data center management is to maximize their profit by minimizing power consumption and service-level agreement (SLA) violations of hosted applications. System dynamics make it difficult to implement optimization in both aspects on shared infrastructures. A majority of existing works either focused on one aspect or applied models that are trained offline for application-specific workload. In addition, virtualization is being widely used in large-scale data centers to attain basic benefits like fault and performance isolation, and to improve system manageability. A key challenge that comes with virtualization is to dynamically provisioning resources for virtual machines and optimize their capacity for meeting service level objectives at the lowest possible cost. In this paper, we present a hierarchical management framework to assure application-level performance while minimizing power consumption for virtualized data centers. A novelty of the management framework is to combine control theory with linear programming technique. Empirical results show that the proposed framework brings substantial energy saving, while ensuring application performance. Especially, the integration of the performance controller and the energy optimizer results in an energy saving of 43% on our hardware testbed.