Self-Optimization in Computer Systems via On-Line Control: Application to Power Management
ICAC '04 Proceedings of the First International Conference on Autonomic Computing
A performance-conserving approach for reducing peak power consumption in server systems
Proceedings of the 19th annual international conference on Supercomputing
Energy-aware server provisioning and load dispatching for connection-intensive internet services
NSDI'08 Proceedings of the 5th USENIX Symposium on Networked Systems Design and Implementation
Power and Performance Management of Virtualized Computing Environments Via Lookahead Control
ICAC '08 Proceedings of the 2008 International Conference on Autonomic Computing
Power-Efficient Response Time Guarantees for Virtualized Enterprise Servers
RTSS '08 Proceedings of the 2008 Real-Time Systems Symposium
Shares and utilities based power consolidation in virtualized server environments
IM'09 Proceedings of the 11th IFIP/IEEE international conference on Symposium on Integrated Network Management
A workload characterization study of the 1998 World Cup Web site
IEEE Network: The Magazine of Global Internetworking
Resource allocation algorithms for virtualized service hosting platforms
Journal of Parallel and Distributed Computing
vGreen: A System for Energy-Efficient Management of Virtual Machines
ACM Transactions on Design Automation of Electronic Systems (TODAES)
AppFlow: Autonomic Performance-Per-Watt Management of Large-Scale Data Centers
GREENCOM-CPSCOM '10 Proceedings of the 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing
DEECO: an ensemble-based component system
Proceedings of the 16th International ACM Sigsoft symposium on Component-based software engineering
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There is growing incentive to reduce the power consumed by data centers. Virtualization is a promising approach to consolidating multiple online services onto a smaller number of computing resources. By dynamically provisioning virtual machines, consolidating the workload, and turning servers on and off as needed, data center operators can maintain desired service-level agreements with end users while achieving higher server utilization and energy efficiency. This paper proposes a distributed cooperative control framework for the power and performance management of virtualized computing environments, and presents some preliminary results aimed at establishing the feasibility of this approach.