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首页> 外文期刊>Journal of computer and system sciences >Optimizing large data transfers in parity-declustered data layouts
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Optimizing large data transfers in parity-declustered data layouts

机译:在奇偶校验分簇的数据布局中优化大型数据传输

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摘要

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.
机译:磁盘阵列可以通过在一组磁盘之间分配数据并允许并行访问来更快地访问用户的数据。磁盘阵列中的容错能力可以通过使用数据布局来实现,奇偶校验解簇技术可以以专用于冗余信息的额外空间为代价,实现更快的故障恢复。奇偶校验减少了数据布局应满足的六个性能条件的集合已指导了大多数以前的工作;但是,在大多数情况下,不能同时满足其中两个条件(最大并行度和大写优化)。这限制了奇偶校验减少的数据布局在大型数据传输期间充分利用可用并行性的能力。对于所有可能的阵列配置,我们提出了同时满足这两个条件的数据布局,并限制了完全满足的偏差。我们的结果为奇偶校验分簇数据布局中的大型数据传输提供了改进的性能保证。

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