An Energy-Efficient Framework for Large-Scale Parallel Storage Systems
Ziliang Zong, Matt Briggs, Nick O'Connor, Xiao Qin · 2007
Huge energy consumption has become a critical bottleneck for further applying large-scale cluster systems to build new data centers. Among various components of a data center, storage subsystems are one of the biggest consumers of energy. In this paper, we propose a novel buffer-disk based framework for large-scale and energy-efficient parallel storage systems. To validate the efficiency of the proposed framework, a buffer-disk scheduling algorithm is designed and implemented. Our algorithm can provide more opportunities for underlying disk power management schemes to save energy by keeping a large number of idle data disks in sleeping mode as long as possible. The trace-driven simulation results based on a revised disksim simulator show that this new framework can significantly improves the energy efficiency of large-scale parallel storage systems.