Abstract
Driven by the growth demand for computational power by science, business and web-application has led to the creation of large-scale data centers which consume enormous amount of power. In this thesis, our goal is to minimize the energy consumption of disk storage systems that used in those datacenters. Specifically, we investigate the approach of using energy-aware disk scheduling algorithm which has been shown as a promising technique to reduce energy without causing significant system overhead and interference. In this work, we focus on the online scheduling solution. Our main contribution is to propose several heuristic online scheduling algorithms and address the following four four important challenges in our approach: (1)request prediction; (2)load variation; (3)limited scheduling resource and (4)write request. We extensively evaluate our solutions using diskSim simulator and workload traces from both real storage systems and synthetic workload generators. The results show our solution can effectively reduce energy using online scheduling techniques and overcome the four challenges in practice.