We construct energy optimization policies for a server cluster, using statistical data analyses and demand prediction methodologies, with an aim to reduce the power consumption of the server cluster. In doing so, we monitor and analyze the historical time-series utilization data of a server cluster. Based on the analyses results, we develop predictions about utilization of servers for future time periods. Using this predictive analysis, we formulate energy optimization rules or policies for the server cluster. These policies are then evaluated to determine if they result in energy savings in the server cluster. High-level implementation of this entire mechanism is provided and a strategy for inclusion of this mechanism in existing data center automation products is discussed.
Published in:
Automation Science and Engineering (CASE), 2010 IEEE Conference on
Date of Conference: 21-24 Aug. 2010