Assuring Demanded Read Performance of Data Deduplication Storage with Backup Datasets

Abstract

Data deduplication has been widely adopted in contemporary backup storage systems. It not only saves storage space considerably, but also shortens the data backup time significantly. Since the major goal of the original data deduplication lies in saving storage space, its design has been focused primarily on improving write performance by removing as many duplicate data as possible from incoming data streams. Although fast recovery from a system crash relies mainly on read performance provided by deduplication storage, little investigation into read performance improvement has been made. In general, as the amount of deduplicated data increases, write performance improves accordingly, whereas associated read performance becomes worse.In this paper, we newly propose a deduplication scheme that assures demanded read performance of each data stream while achieving its write performance at a reasonable level, eventually being able to guarantee a target system recovery time. For this, we first propose an indicator called cacheaware Chunk Fragmentation Level (CFL) that estimates degraded read performance on the fly by taking into account both incoming chunk information and read cache effects. We also show a strong correlation between this CFL and read performance in the backup datasets. In order to guarantee demanded read performance expressed in terms of a CFL value, we propose a read performance enhancement scheme called selective duplication that is activated whenever the current CFL becomes worse than the demanded one. The key idea is to judiciously write non-unique (shared) chunks into storage together with unique chunks unless the shared chunks exhibit good enough spatial locality. We quantify the spatial locality by using a selective duplication threshold value. Our experiments with the actual backup datasets demonstrate that the proposed scheme achieves demanded read performance in most cases at the reasonable cost of write performance.

Survey on Data Deduplication for Cloud Storage to Reduce Fragmentation

“…They enumerate the spatial area by using a selective duplication threshold value. Their experiments with the actual backup datasets determine that the proposed scheme achieves requested read performance in most cases at the realistic cost of write performance [8].…”

Survey on Fragmentation for Deduplication in Backup Storage

“…J. Nam, D. Park, and D. H. Du [2], author proposed a novel indicator for dedupe scheme. They proposed scheme provides two-fold approach, first, a novel indicator for dedupe scheme called cache-aware Chunk Fragmentation Level (CFL) monitor and second selective duplication for improvement read performance.…”

“…Proposed scheme assures demanded read performance of each data stream while completing its write performance at a practical level and also certain a target system recovery time. Major drawback of selective duplication is that it requires extra memory space called in-memory temp container [2].…”

RevDedup

“…It also provides space-efficient VM image storage since VM images have high content similarities [5]. However, deduplication has a drawback of introducing fragmentation [6,8,10,14,15], since some blocks of a file may now refer to other identical blocks of a different file. To illustrate, Figure 1(a) shows three snapshots of a VM, denoted by VM 1 , VM 2 , and VM 3 , which are to be written to disk that initially has no data.…”

“…On the other hand, we believe that achieving high read throughput is necessary in any backup system. For instance, a fast restore operation can minimize the system downtime during disaster recovery [10,16].…”