A highly reliable and parallelizable data distribution scheme for data grids
Future Generation Computer Systems
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When a RAID-5 volume is scaled up with added disks, data have to be redistributed from original disks to all disks including the original and the new. Existing online scaling techniques suffer from long redistribution times as well as negative impacts on application performance. By leveraging our insight into a reordering window, this paper presents ALV, a new data redistribution approach to RAID-5 scaling. The reordering window is a result of the natural space hole as data being redistributed, and it grows in size. The data inside the reordering window can migrate in any order without overwriting other in-use data chunks. The ALV approach exploits three novel techniques. First, ALV changes the movement order of data chunks to access multiple successive chunks via a single I/O. Second, ALV updates mapping metadata lazily to minimize the number of metadata writes while ensuring data consistency. Third, ALV uses an on/off logical valve to adaptively adjust the redistribution rate depending on application workload. We implemented ALV in Linux Kernel 2.6.18 and evaluated its performance by replaying three real-system traces: TPC-C, Cello-99, and SPC-Web. The results demonstrated that ALV outperformed the conventional approach consistently by 53.31-73.91 percent in user response time and by 24.07-29.27 percent in redistribution time.