ACDC '09 Proceedings of the 1st workshop on Automated control for datacenters and clouds
Dynamic optimization of power and performance for virtualized server clusters
Proceedings of the 2010 ACM Symposium on Applied Computing
A dynamic optimization model for power and performance management of virtualized clusters
Proceedings of the 1st International Conference on Energy-Efficient Computing and Networking
A distributed control framework for performance management of virtualized computing environments
Proceedings of the 7th international conference on Autonomic computing
Simultaneous thermal and timeliness guarantees in distributed real-time embedded systems
Journal of Systems Architecture: the EUROMICRO Journal
DynaQoS: model-free self-tuning fuzzy control of virtualized resources for QoS provisioning
Proceedings of the Nineteenth International Workshop on Quality of Service
Proceedings of the 9th international conference on Autonomic computing
Computers and Industrial Engineering
Setting energy efficiency goals in data centers: the GAMES approach
E2DC'12 Proceedings of the First international conference on Energy Efficient Data Centers
TEStore: exploiting thermal and energy storage to cut the electricity bill for datacenter cooling
Proceedings of the 8th International Conference on Network and Service Management
Energy-efficient virtual machine scheduling in performance-asymmetric multi-core architectures
Proceedings of the 8th International Conference on Network and Service Management
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Both power and performance are important concerns for enterprise data centers. While various management strategies have been developed to effectively reduce server power consumption by transitioning hardware components to lower-power states, they cannot be directly applied to today's data centers that rely on virtualization technologies. Virtual machines running on the same physical server are correlated, because the state transition of any hardware component will affect the application performance of all the virtual machines. As a result, reducing power solely based on the performance level of one virtual machine may cause another to violate its performance specification. This paper proposes a two-layer control architecture based on well-established control theory. The primary control loop adopts a multi-input-multi-output control approach to maintain load balancing among all virtual machines so that they can have approximately the same performance level relative to their allowed peak values. The secondary performance control loop then manipulates CPU frequency for power efficiency based on the uniform performance level achieved by the primary loop. Empirical results demonstrate that our control solution can effectively reduce server power consumption while achieving required application-level performance for virtualized enterprise servers.