Adaptive disk spin-down for mobile computers

We address the problem of deciding when to spin down the disk of a mobile c omputer in order to extend battery life. One of the most critical resources in mobile computing environments is battery life, and good energy conserva tion methods increase the utility of mobile systems. We use a simple and ef ficient algorithm based on machine learning techniques that has excellent p erformance. Using trace data, the algorithm outperforms several methods tha t are theoretically optimal under various worst-case assumptions, as well a s the best fixed time-out strategy. In particular, the algorithm reduces th e power consumption of the disk to about half of the energy consumed by a o ne minute fixed time-out policy. Furthermore, the algorithm uses as little as 88% of the energy consumed by the best fixed time-out computed in retros pect.