Name
Abstract | ||
|---|---|---|
In large scale data storage systems, RAID-6 has received more attention due to its capability to tolerate concurrent failures of any two disks, providing a higher level of reliability. However, a challenging issue is its scalability, or how to efficiently expand the disks. The main reason causing this problem is the typical fault tolerant scheme of most RAID-6 systems known as Maximum Distance Separable (MDS) codes, which offer data protection against disk failures with optimal storage efficiency but they are difficult to scale. To address this issue, we propose a novel Stripe-based Data Migration (SDM) scheme for large scale storage systems based on RAID-6 to achieve higher scalability. SDM is a stripe-level scheme, and the basic idea of SDM is optimizing data movements according to the future parity layout, which minimizes the overhead of data migration and parity modification. SDM scheme also provides uniform data distribution, fast data addressing and migration. We have conducted extensive mathematical analysis of applying SDM to various popular RAID-6 coding methods such as RDP, P-Code, H-Code, HDP, X-Code, and EVENODD. The results show that, compared to existing scaling approaches, SDM decreases more than 72.7% migration I/O operations and saves the migration time by up to 96.9%, which speeds up the scaling process by a factor of up to 32. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/CLUSTER.2012.24 | CLUSTER |
Keywords | Field | DocType |
optimisation,fault tolerant scheme,scaling process,data migration,data addressing,data privacy,raid,scalability,fast data,raid-6,mds code,maximum distance separable,stripe-based data migration scheme,fault tolerant computing,storage allocation,mathematical analysis,migration time,large scale data storage,disk failure,performance evaluation,data movement optimization,failure analysis,sdm scheme,data movement,reliability,optimal storage efficiency,redundancy,uniform data distribution,data protection,raid-6 system,data storage system,raid-6 coding method,labeling,layout,encoding,acceleration | Computer science,Computer data storage,Parallel computing,Coding (social sciences),Real-time computing,Storage efficiency,Redundancy (engineering),Fault tolerance,RAID,Data migration,Scalability,Distributed computing | Conference |
ISSN | ISBN | Citations |
1552-5244 | 978-1-4673-2422-9 | 14 |
PageRank | References | Authors |
0.62 | 17 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chentao Wu | 1 | 130 | 21.00 |
| Xubin He | 2 | 747 | 63.49 |
| Jizhong Han | 3 | 355 | 54.72 |
| Huailiang Tan | 4 | 31 | 3.97 |
| Changsheng Xie | 5 | 25 | 6.27 |