Using power trend predicator to improve datacenter thermal management efficiency

This paper introduced one optimized proactive cooling management approach based on power variation trend analysis. Through analyzing the data center historical power telemetries, the power predictor is able to predicate power variation with 5– 15 minutes granularity. The cooling controller uses the observed heat information and estimated thermal variation trend to drive CRAC to manage temperature situation at prediction window. To validate cooling results from different cooling parameters, one risk level evaluation method is proposed and the experiments for different prediction window are conducted and the result is presented.