Thinraid: Thinning Down Raid Array For Energy Conservation
Keywords
Energy efficient; RAID; Stripe degradation
Abstract
The current power managements in RAID array are mostly designed to conserve energy by spinning down partial disks of standard RAID architecture. However, spinning down several disks not only decreases disk parallelism, but also creates new problems, for example, partial chunks of the stripe cannot be accessed directly or multiple chunks of the same stripe are stored on the same disk, which affect spatial locality. We refer these problems as stripe degradation, which results in further performance degradation. To avoid such problems, this paper proposes a new RAID storage architecture called ThinRAID, which uses a subset of disks to build a capacity-Adaptive RAID array based on the volume of the data set. Also, the other non-essential disks are spun down to save energy. When the workload is projected to become heavier based on our forecast model, data are migrated to disks that have recently transitioned from standby to active. Furthermore, we also propose a novel data reorganization algorithm that can minimize data migration. We have implemented ThinRAID in the Linux kernel and evaluated its performance and energy efficiency by replaying seven representative traces. Experimental results show that ThinRAID can save 15-27 percent on energy on average over conventional RAID, with minimum performance degradation. In comparison to PARAID, ThinRAID achieves up to 62 percent performance improvement.
Publication Date
10-1-2015
Publication Title
IEEE Transactions on Parallel and Distributed Systems
Volume
26
Issue
10
Number of Pages
2903-2915
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/TPDS.2014.2360696
Copyright Status
Unknown
Socpus ID
84961784102 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84961784102
STARS Citation
Wan, Jiguang; Qu, Xiaoyang; Zhao, Nannan; Wang, Jun; and Xie, Changsheng, "Thinraid: Thinning Down Raid Array For Energy Conservation" (2015). Scopus Export 2015-2019. 673.
https://stars.library.ucf.edu/scopus2015/673