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Proceedings of the conference on Design, automation and test in Europe - DATE '08
The effectiveness of stochastic power management relies on the accurate system and workload model and effective policy optimization. Workload modeling is a machine learning procedure that finds the intrinsic pattern of the incoming tasks based on the observed workload attributes. Markov Decision Process (MDP) based model has been widely adopted for stochastic power management because it delivers provable optimal policy. Given a sequence of observed workload attributes, the hidden Markov modeldoi:10.1145/1403375.1403402 fatcat:ebgup6x6yjdrbmzsvv6be2r2ta