IEEE Spectrum
Ensemble-level Power Management for Dense Blade Servers
Proceedings of the 33rd annual international symposium on Computer Architecture
Exploiting Platform Heterogeneity for Power Efficient Data Centers
ICAC '07 Proceedings of the Fourth International Conference on Autonomic Computing
VirtualPower: coordinated power management in virtualized enterprise systems
Proceedings of twenty-first ACM SIGOPS symposium on Operating systems principles
Weatherman: Automated, Online and Predictive Thermal Mapping and Management for Data Centers
ICAC '06 Proceedings of the 2006 IEEE International Conference on Autonomic Computing
Future Generation Computer Systems
Power Aware Meta Scheduler for Adaptive VM Provisioning in IaaS Cloud
International Journal of Cloud Applications and Computing
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Power efficiency is a major concern in operating cloud data centers. It affects operational costs and return on investment, with a profound impact on the environment. Current data center operating environments, such as management consoles and cloud control software, tend to optimize for performance and service level agreements and ignore power implications when evaluating workload scheduling choices. We believe that power should be elevated to the first-order consideration in data-center management and that operators should be provided with insights and controls necessary to achieve that purpose. In this paper we describe several foundational techniques for group-level power management that result in significant power savings in large data centers with run-time load allocation capability, such as clouds and virtualized data centers. We cover VM migration to save power, server pooling or platooning to balance power savings with startup times so as not to impair performance, and discuss power characteristics of servers that affect both the limits and the opportunities for power savings.