A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf
.
A framework of stochastic power management using hidden Markov model
2008
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 model
doi:10.1145/1403375.1403402
fatcat:ebgup6x6yjdrbmzsvv6be2r2ta