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REO: A Generic RAID Engine and Optimizer
Present day applications that require reliable data storage use one of five commonly available RAID levels to protect against data loss due to media or disk failures. With a marked rise in the quantity of stored data and no commensurate improvement in disk reliability, a greater variety is becoming necessary to contain costs. Adding new RAID codes to an implementation becomes cost prohibitive since they require significant development, testing and tuning efforts. We suggest a novel solution to this problem: a generic RAID Engine and Optimizer (REO). It is generic in that it works for any XOR-based erasure (RAID) code and under any combination of sector or disk failures. REO can systematically deduce a least cost reconstruction strategy for a read to lost pages or for an update strategy for a flush of dirty pages. Using trace driven simulations we show that REO can automatically tune I/O performance to be competitive with existing RAID implementations.
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