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Adaptive disk spindashdown for mobile computers

David P. Helmbold, Darrell D.E. Long, Tracey L. Sconyers and Bruce Sherrod

Abstract  We address the problem of deciding when to spin down the disk of a mobile computer in order to extend battery life. One of the most critical resources in mobile computing environments is battery life, and good energy conservation methods increase the utility of mobile systems. We use a simple and efficient algorithm based on machine learning techniques that has excellent performance. Using trace data, the algorithm outperforms several methods that are theoretically optimal under various worstdashcase assumptions, as well as the best fixed timedashout strategy. In particular, the algorithm reduces the power consumption of the disk to about half of the energy consumed by a one minute fixed timedashout policy. Furthermore, the algorithm uses as little as 88% of the energy consumed by the best fixed timedashout computed in retrospect.

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