With the rapid growth of the production and storage of large scale data sets it is important to investigate methods to drive the cost of storage systems down. We are currently in the midst of an information explosion and large scale storage centers are increasingly used to help store generated data. There are several methods to bring the cost of large scale storage centers down and we investigate a technique that focuses on transitioning storage disks into lower power states. To achieve this goal this dissertation introduces a model of disk systems that leverages disk access patterns to prefetch popular sets of data to produce energy saving opportunities.
Using our model, we have developed a simulator that allows us to quickly change various parameters to investigate the relationship that file access patterns, disk energy parameters, and simulation parameters have on the overall energy efficiency of disk systems. To help improve the validity of our simulation results we leveraged the validated disk simulator, DiskSim, and added disk power models to DiskSim. This allowed us to test our energy efficient strategies with a validated storage system simulator.
The last part of this dissertation focuses on implementing a large scale storage system virtual file system. We introduce the Energy Efficient Virtual File System, or EEVFS, to manage the data placement and disk states in a cluster storage system. Our modeling and simulation results indicated that large data sizes and knowledge about the disk access pattern are valuable for storage system energy savings techniques. Storage servers that support applications that stream media is one key area that would benefit from our strategies. The last chapter of the dissertation introduces the concept of parallel striping groups, which attempt to improve the performance of EEVFS while maintaining energy savings.
|School Location:||United States -- Alabama|
|Source:||DAI-B 71/08, Dissertation Abstracts International|
|Keywords:||Energy conservation, Prefetching, Virtual file systems|
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