Can We Really Recover Data if Storage Subsystem Fails?

Xiao, Weijun; Yang, Qing

doi:10.1109/icdcs.2008.38

Cited by 7 publications

(3 citation statements)

References 13 publications

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“…Spring and Wetherall proposed a technique to identify repetitive information of network traffic such as web proxy caching [ 36 ]. Yang et al leverage content similarity for write requests to reduce storage space for recovery [37][38] [39]. Delta encoding has been used to extend the redundancy reduction research to similar data blocks, not only for identical blocks [40] [41].…”

Section: Content Redundancy Reductionmentioning

confidence: 99%

A New Buffer Cache Design Exploiting Both Temporal and Content Localities

Ren

Yang

2010

2010 IEEE 30th International Conference on Distributed Computing Systems

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This paper presents a Least Popularly Used buffer cache algorithm to exploit both temporal locality and content locality of I/O requests. Popular data blocks are selected as reference blocks that are not only accessed frequently but also identical or similar in content to other blocks that are being accessed. Fast delta compression and decompression are used to satisfy as many I/O requests as possible using the popular reference blocks together with small deltas inside the buffer cache. The popularity of a reference block is calculated based on the statistical analysis of data contents and access frequency. A prototype LPU has been implemented as a new cache layer for Kernel Virtual Machine (KVM) on Linux system. Experimental results show LPU is effective for a variety of workloads with the maximum speed up of over 300% compared with LRU.

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Section: Content Redundancy Reductionmentioning

confidence: 99%

A New Buffer Cache Design Exploiting Both Temporal and Content Localities

Ren

Yang

2010

2010 IEEE 30th International Conference on Distributed Computing Systems

Self Cite

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“…Unfortunately, the issue of read performance has received very little attention in the literature. For example, in backup recovery, only 33% of recovery cases are successful [Xiao and Yang 2008], and 48% of organizations need to reduce recovery times [ESG 2008]. In the VM servers, read performance is arguably even more important, particularly in primary storage systems and the cloud environment where the restores from the VM suspensions and migrations are very frequent and directly reflect the quality of the cloud services as perceived by clients.…”

Section: Introductionmentioning

confidence: 99%

Read-Performance Optimization for Deduplication-Based Storage Systems in the Cloud

Mao

Jiang

et al. 2014

ACM Trans. Storage

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Data deduplication has been demonstrated to be an effective technique in reducing the total data transferred over the network and the storage space in cloud backup, archiving, and primary storage systems, such as VM (virtual machine) platforms. However, the performance of restore operations from a deduplicated backup can be significantly lower than that without deduplication. The main reason lies in the fact that a file or block is split into multiple small data chunks that are often located in different disks after deduplication, which can cause a subsequent read operation to invoke many disk IOs involving multiple disks and thus degrade the read performance significantly. While this problem has been by and large ignored in the literature thus far, we argue that the time is ripe for us to pay significant attention to it in light of the emerging cloud storage applications and the increasing popularity of the VM platform in the cloud. This is because, in a cloud storage or VM environment, a simple read request on the client side may translate into a restore operation if the data to be read or a VM suspended by the user was previously deduplicated when written to the cloud or the VM storage server, a likely scenario considering the network bandwidth and storage capacity concerns in such an environment.To address this problem, in this article, we propose SAR, an SSD (solid-state drive)-Assisted Read scheme, that effectively exploits the high random-read performance properties of SSDs and the unique data-sharing characteristic of deduplication-based storage systems by storing in SSDs the unique data chunks with high reference count, small size, and nonsequential characteristics. In this way, many read requests to HDDs are replaced by read requests to SSDs, thus significantly improving the read performance of the deduplicationbased storage systems in the cloud. The extensive trace-driven and VM restore evaluations on the prototype implementation of SAR show that SAR outperforms the traditional deduplication-based and flash-based cache schemes significantly, in terms of the average response times.

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“…Because of such lack of understanding, a large percentage of data recoveries based on snapshots failed in the real world [4]. While this fact is well known, there has been no research study on why this is the case except for our recent analytical study that uncovered several important unknown issues [5]. Therefore, we believe that it is very important to understand how snapshot techniques work and how they protect and recover data.…”

Section: Introductionmentioning

confidence: 99%

Design and Analysis of Block-Level Snapshots for Data Protection and Recovery

Xiao

Yang

Ren

et al. 2009

IEEE Trans. Comput.

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Abstract-This paper presents a comprehensive study on implementations and performance evaluations of two snapshot techniques: copy-on-write snapshot and redirect-on-write snapshot. We develop a simple Markov process model to analyze data block behavior and its impact on application performance, while the snapshot operation is underway at the block-level storage. We have implemented the two snapshots techniques on both Windows and Linux operating systems. Based on our analytical model and our implementation, we carry out quantitative performance evaluations and comparisons of the two snapshot techniques using IoMeter, PostMark, TPC-C, and TPC-W benchmarks. Our measurements reveal many interesting observations regarding the performance characteristics of the two snapshot techniques. Depending on the applications and different I/O workloads, the two snapshot techniques perform quite differently. In general, copy-on-write performs well on read-intensive applications, while redirect-on-write performs well on writeintensive applications.

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Can We Really Recover Data if Storage Subsystem Fails?

Abstract: Abstract

Cited by 7 publications

References 13 publications

A New Buffer Cache Design Exploiting Both Temporal and Content Localities

A New Buffer Cache Design Exploiting Both Temporal and Content Localities

Read-Performance Optimization for Deduplication-Based Storage Systems in the Cloud

Design and Analysis of Block-Level Snapshots for Data Protection and Recovery

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