Energy Smart Management of Scientific Data

Scientific data centers comprised of high-powered computing equipment and large capacity disk storage systems consume considerable amount of energy. Dynamic power management techniques (DPM) are commonly used for saving energy in disk systems. These involve powering down disks that exhibit long idle periods and placing them in standby mode. A file request from a disk in standby mode will incur both energy and performance penalties as it takes energy (and time) to spin up the disk before it can serve a file. For this reason, DPM has to make decisions as to when to transition the disk into standby mode such that the energy saved is greater than the energy needed to spin it up again and the performance penalty is tolerable. The length of the idle period until the DPM decides to power down a disk is called idlenessthreshold. In this paper, we study both analytically and experimentally dynamic power management techniques that save energy subject to performance constraints on file access costs. Based on observed workloads of scientific applications and disk characteristics, we provide a methodology for determining file assignment to disks and computing idleness thresholds that result in significant improvements to the energy saved by existing DPMsolutions while meeting response time constraints. We validate our methods with simulations that use traces taken from scientific applications