[LCTES'23] Rep-RAID: An Integrated Approach to Optimizing Data Replication and Garbage Collection(…)

Rep-RAID: An Integrated Approach to Optimizing Data Replication and Garbage Collection in RAID-Enabled SSDs (Video, LCTES 2023)
Jun Li, Balazs Gerofi, Francois Trahay, Zhigang Cai, and Jianwei Liao
(Southwest University, China / National Institute of Informatics, Japan; Intel Corporation, USA; Telecom SudParis, France; Southwest University, China; Southwest University, China)
Abstract: Redundant Array of Independent Disks (RAID) technology has been recently introduced to flash memory based SSDs to enhance their data reliability. Although RAID increases reliability, it doubles the number of write operations and requires additional parity computation as every write operation on a data chunk leads to another update on the corresponding parity chunk. Data replication has been proposed to mitigate the overhead of write requests in RAID enabled SSDs, however, replication increases the cost of garbage collection (GC), which in turn limits the improvement of I/O performance compared to the baseline RAID implementation.
This paper introduces Rep-RAID, an improved data replication management scheme accompanied with optimized GC for RAID-enabled SSDs. Guided by a mathematical model, Rep-RAID only replicates frequently updated data chunks. Furthermore, Rep-RAID reorganizes new data stripes during the GC process by utilizing replicated data to replace invalid data chunks caused by data replication in old stripes. As a result, it decreases I/O latency for both read and write requests and significantly reduces the GC overhead induced by data movement. Experimental results show that the proposed scheme can improve I/O performance by 16.7%, and reduce tail latency by up to 17.9% at the 99.99th percentile, when compared to the state-of-the-art RAID-enabled SSDs.
Article: doi.org/10.114...
ORCID: orcid.org/0000..., orcid.org/0009..., orcid.org/0000..., orcid.org/0000..., orcid.org/0000...
Video Tags: SSDs, RAID-5, Replication, Garbage Collection, Stripe Reorganization, lctes23main-p24-p, doi:10.1145/3589610.3596274, orcid:0000-0001-5235-6496, orcid:0009-0004-8585-6031, orcid:0000-0001-7329-1812, orcid:0000-0002-8406-8461, orcid:0000-0001-6149-6650
Presentation at the LCTES 2023 conference, June 18, 2023, pldi23.sigplan...
Sponsored by ACM SIGBED, ACM SIGPLAN,