Performance aware energy efficient storage systems

Trends in Internet infrastructure are driving towards using data centers to provide services such as web hosting and outsourced storage. Data centers typically have high power requirements and may require as much electricity as an entire city. This makes energy a growing consideration in the Total Cost of Ownership for data centers. Among all components, disk storage is one of the biggest energy consumers. For a typical medium-sized data center, disk drives would represent an electricity budget of ;Designing an energy-efficient high-end storage system is a challenging task. Conserving energy usually incurs performance penalty; however, performance is very critical in data centers as they must meet response-time Service Level Agreement they provide to customers. Moreover, compared to single disk systems, high-end storage systems consisting of hundreds or thousands of disks is much more complex. All components including storage cache management, disk power control and data layout need to be carefully designed to minimize disk energy consumption in a performance-conscious manner.;In this dissertation, we present the design of a performance-aware energy-efficient storage system in data centers. We achieve this by combining a number of novel techniques: power-aware storage cache replacement algorithms and write polices that can provide more opportunities for underlying disk power management to save energy; a coarse-grain global control algorithm that optimally determines the power configuration for each disk to minimize energy consumption based on the specified performance goal; a self-adaptive, performance-directed and energy-efficient data layout which dynamically balances between performance and energy conservation as workloads change; a performance guarantee method that automatically boosts performance if there is a risk that performance goals might not be met due to disk power management.;Our simulation results using both file system and online transaction processing (OLTP) traces show that our system can provide up to 65% energy savings while still meeting the response-time performance requirements (6.5-26 times better than previous solutions).