Workload-Aware Elastic Striping With Hot Data Identification for SSD RAID Arrays

Redundant array of independent disk (RAID) offers a good option to provide device-level fault tolerance for solid-state drives (SSDs). However, parity update with either read–modify–write or read–reconstruct–write may introduce a lot of extra I/Os and thus significantly degrades SSD RAID performance. To reduce the parity update cost, elastic striping chooses to reconstruct new stripes with only the newly updated data chunks instead of directly updating parity chunks. However, it necessitates an RAID-level garbage collection (GC) process, which may incur a very high cost due to the mixture of hot and cold data chunks. To address this problem, we follow the idea of elastic striping and propose a workload-aware scheme (WAS) to reduce the RAID-level GC cost so as to improve the performance and endurance of SSD RAID. In particular, we first develop a novel lightweight hot data identification scheme which requires only a very small computation time and memory cost, then propose a hotness-aware elastic striping approach to separately write data chunks with different hotness to different regions in SSD RAID. To evaluate the effectiveness and efficiency of our WAS, we implement a prototype system on RAID-5 and RAID-6 arrays composed of commercial SSDs. Experimental results show that compared to original elastic striping, our scheme reduces 30.0%–70.6% (and 23.9%–63.2%) of chunk writes under the RAID-5 (and RAID-6) settings, and also reduces the average response time by 60.9%–79.3% (and 56.8%–80.9%) for RAID-5 (and RAID-6), respectively. Besides, our scheme also improves the endurance and reliability of SSD RAID compared to original elastic striping.