Parallel disk systems consume a significant amount of energy due to the large number of disks. To design economically attractive and environmentally friendly parallel disk systems, in this paper we design and evaluate an energy-aware prefetching strategy for parallel disk systems consisting of a small number of buffer disks and large number of data disks. Using buffer disks to temporarily handle requests for data disks, we can keep data disks in the low-power mode as long as possible. Our prefetching algorithm aims to group many small idle periods in data disks to form large idle periods, which in turn allow data disks to remain in the standby state to save energy. To achieve this goal, we utilize buffer disks to aggressively fetch popular data from regular data disks into buffer disks, thereby putting data disks into the standby state for longer time intervals. A centrepiece in the prefetcing mechanism is an energy-saving prediction model, based on which we implement the energy-saving calculation module that is invoked in the prefetching algorithm. We quantitatively compare our energy-aware prefetching mechanism against existing solutions, including the dynamic power management strategy. Experimental results confirm that the buffer-disk-based prefetching can significantly reduce energy consumption in parallel disk systems by up to 50 percent. In addition, we systematically investigate the energy efficiency impact that varying disk power parameters has on our prefetching algorithm.
['Adam Manzanres', 'Xiaojun Ruan', 'Shu Yin', 'Mais Nijim', 'Wei Luo', 'Xiao Qin']
Energy-Aware Prefetching for Parallel Disk Systems: Algorithms, Models, and Evaluation