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Nowadays, one of the most important goals of data center management is to maximize their profit by minimizing power consumption and service-level agreement violations of hosted applications. System dynamics make it difficult to implement optimization in both aspects on shared infrastructures. Virtualization is being widely used in large-scale data centers to attain basic benefits like fault and performance isolation, and to improve system manageability. Server consolidation based on virtualization is an important technique for improving power efficiency in data centers. 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 propose an integrated management solution which takes advantages of both virtual machine resizing and server consolidation to achieve energy efficiency and quality of service in virtualized data centers. A novelty of the solution is to integrate linear programming, ant colony optimization and control theory techniques. We evaluate the effectiveness of the approach applied to a server cluster testbed. Empirical results show that our approach conserves about 47% of the energy required by a system designed for peak workload scenario, while ensuring application performance.

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