Optimizing large data transfers in parity-declustered data layouts

Disk arrays allow faster access to users' data by distributing the data among a collection of disks and allowing parallel access. Fault tolerance in a disk array can be achieved by using a data layout, and the technique of parity declustering allows faster failure recovery at the cost of additional space dedicated to redundant information. A collection of six performance conditions that parity-declustered data layouts should satisfy has guided most previous work; however two of these conditions (Maximal parallelism and Large write optimization) cannot be jointly satisfied in most cases. This limits the ability of parity-declustered data layouts to take full advantage of the available parallelism during large data transfers. We present data layouts that approximately satisfy these two conditions simultaneously for all possible array configurations, and bound the deviations from complete satisfaction. Our results yield improved performance guarantees for large data transfers in parity-declustered data layouts.