Ripple-RAID: A high-performance and energy-efficient raid for continuous data storage

Zhi Zhuo Sun, Quan Xin Zhang*, Yu An Tan, Yuan Zhang Li

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

The applications, such as video surveillance, backup and archiving, have inherent workload characteristic and I/O access pattern, and require specialized optimization for storage energy saving. Partial parallelism in RAID is beneficial to storage energy saving, but generally makes RAID perform small writes, which heavily deteriorates the performance. A high-performance and energy-efficient RAID, Ripple-RAID, is proposed for these applications. A new partial-parallel data layout is presented, and by comprehensively employing strategies such as address mapping, out-place update, generating parity data progressively based on pipeline, and segmented data recovery, Ripple-RAID not only obtains energy efficiency of partial parallelism but also eliminates the small writes incurred by partial parallelism while providing single disk fault tolerance. When write workload is 80% sequential and transfer request size is 512KB, the write performance of Ripple-RAID is 3.9 times that of S-RAID 5, 1.9 times that of Hibernator and MAID, and 0.49 times that of PARAID and eRAID 5; meanwhile its energy consumption is 20% less than S-RAID 5, 33% less than Hibernator and MAID, 70% less than eRAID 5, and 72% less than PARAID.

Original languageEnglish
Pages (from-to)1824-1839
Number of pages16
JournalRuan Jian Xue Bao/Journal of Software
Volume26
Issue number7
DOIs
Publication statusPublished - 1 Jul 2015

Keywords

  • Archiving
  • Continuous data storage
  • Energy efficiency
  • High performance
  • RAID
  • Video surveillance

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