%A Linjun MEI, Dan FENG, Lingfang ZENG, Jianxi CHEN, Jingning LIU %T Exploiting flash memory characteristics to improve performance of RAIS storage systems %0 Journal Article %D 2019 %J Front. Comput. Sci. %J Frontiers of Computer Science %@ 2095-2228 %R 10.1007/s11704-018-7009-0 %P 913-928 %V 13 %N 5 %U {https://journal.hep.com.cn/fcs/EN/10.1007/s11704-018-7009-0 %8 2019-10-15 %X

Redundant array of independent SSDs (RAIS) is generally based on the traditional RAID design and implementation. The random small write problem is a serious challenge of RAIS. Random small writes in parity-based RAIS systems generate significantly more pre-reads and writes which can degrade RAIS performance and shorten SSD lifetime. In order to overcome the well-known write-penalty problem in the parity-based RAID5 storage systems, several logging techniques such as Parity Logging and Data Logging have been put forward. However, these techniques are originally based on mechanical characteristics of the HDDs, which ignore the properties of the flash memory.

In this article, we firstly propose RAISL, a flash-aware logging method that improves the small write performance of RAIS storage systems. RAISL writes new data instead of new data and pre-read data to the log SSD by making full use of the invalid pages on the SSD of RAIS. RAISL does not need to perform the pre-read operations so that the original characteristics of workloads are kept. Secondly, we propose AGCRL on the basis of RAISL to further boost performance. AGCRL combines RAISL with access characteristic to guide read and write cost regulation to improve the performance of RAIS storage systems. Our experiments demonstrate that the RAISL significantly improves write performance and AGCRL improves both of write performance and read performance. AGCRL on average outperforms RAIS5 and RAISL by 39.15% and 16.59% respectively.