Power routing: dynamic power provisioning in the data center
Proceedings of the fifteenth edition of ASPLOS on Architectural support for programming languages and operating systems
Power Aware Resource Allocation in Virtualized Environments through VM Behavior Identification
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
Coordinating processor and main memory for efficientserver power control
Proceedings of the international conference on Supercomputing
Capping the electricity cost of cloud-scale data centers with impacts on power markets
Proceedings of the 20th international symposium on High performance distributed computing
How much power oversubscription is safe and allowed in data centers
Proceedings of the 8th ACM international conference on Autonomic computing
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Genetic and Evolutionary Computation Conference
Leveraging thermal storage to cut the electricity bill for datacenter cooling
HotPower '11 Proceedings of the 4th Workshop on Power-Aware Computing and Systems
ReRack: power simulation for data centers with renewable energy generation
ACM SIGMETRICS Performance Evaluation Review
iSwitch: coordinating and optimizing renewable energy powered server clusters
Proceedings of the 39th Annual International Symposium on Computer Architecture
The Journal of Supercomputing
PEPON: performance-aware hierarchical power budgeting for NoC based multicores
Proceedings of the 21st international conference on Parallel architectures and compilation techniques
Proceedings of the 9th international conference on Autonomic computing
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
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In today's data centers, precisely controlling server power consumption is an essential way to avoid system failures caused by power capacity overload or overheating due to increasingly high server density. While various power control strategies have been recently proposed, existing solutions are not scalable to control the power consumption of an entire large-scale data center, because these solutions are designed only for a single server or a rack enclosure. In a modern data center, however, power control needs to be enforced at three levels: rack enclosure, power distribution unit, and the entire data center, due to the physical and contractual power limits at each level. This paper presents SHIP, a highly scalable hierarchical power control architecture for large-scale data centers. SHIP is designed based on well-established control theory for analytical assurance of control accuracy and system stability. Empirical results on a physical testbed show that our control solution can provide precise power control, as well as power differentiations for optimized system performance. In addition, our extensive simulation results based on a real trace file demonstrate the efficacy of our control solution in large-scale data centers composed of thousands of servers.