Design and Evaluation of a New Approach to RAID-0 Scaling
Scaling up a RAID-0 volume with added disks can increase its storage capacity and I/O bandwidth simultaneously. For preserving a round-robin data distribution, existing scaling approaches require all the data to be migrated. Such large data migration results in a long redistribution time as well as a negative impact on application performance. In this article, we present a new approach to RAID-0 scaling called FastScale. First, FastScale minimizes data migration, while maintaining a uniform data distribution. It moves only enough data blocks from old disks to fill an appropriate fraction of new disks. Second, FastScale optimizes data migration with access aggregation and lazy checkpoint. Access aggregation enables data migration to have a larger throughput due to a decrement of disk seeks. Lazy checkpoint minimizes the number of metadata writes without compromising data consistency. Using several real system disk traces, we evaluate the performance of FastScale through comparison with SLAS, one of the most efficient existing scaling approaches. The experiments show that FastScale can reduce redistribution time by up to 86.06% with smaller application I/O latencies. The experiments also illustrate that the performance of RAID-0 scaled using FastScale is almost identical to, or even better than, that of the round-robin RAID-0.
design data migration performance access aggregation lazy checkpoint algorithms experimentation management raid scaling