Exploiting redundancy to boost performance in a RAID-10 style cluster-based file system

Zhu, Yan; Jiang, Hong; Qin, Xiao; Feng, Dan; Swanson, David

doi:10.1007/s10586-006-0011-6

Cited by 4 publications

(4 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A similar microbenchmark is also used to evaluate the read performance [65,66]. In addition, we propose to use the techniques of doubling the degree of parallelism and hot-spot skipping to improve the aggregate read performance.…”

Section: Read Performance and Real Application Benchmarkmentioning

confidence: 99%

CEFT: A cost-effective, fault-tolerant parallel virtual file system

Zhu

Jiang

2006

Journal of Parallel and Distributed Computing

Self Cite

View full text Add to dashboard Cite

The vulnerability of computer nodes due to component failures is a critical issue for cluster-based file systems. This paper studies the development and deployment of mirroring in cluster-based parallel virtual file systems to provide fault tolerance and analyzes the tradeoffs between the performance and the reliability in the mirroring scheme. It presents the design and implementation of CEFT, a scalable RAID-10 style file system based on PVFS, and proposes four novel mirroring protocols depending on whether the mirroring operations are server-driven or client-driven, whether they are asynchronous or synchronous. The comparisons of their write performances, measured in a real cluster, and their reliability and availability, obtained through analytical modeling, show that these protocols strike different tradeoffs between the reliability and performance. Protocols with higher peak write performance are less reliable than those with lower peak write performance, and vice versa. A hybrid protocol is proposed to optimize this tradeoff.

show abstract

Section: Read Performance and Real Application Benchmarkmentioning

confidence: 99%

CEFT: A cost-effective, fault-tolerant parallel virtual file system

Zhu

Jiang

2006

Journal of Parallel and Distributed Computing

Self Cite

View full text Add to dashboard Cite

show abstract

“…As data throughput is the most important objective of PVFS, some expensive but indispensable functions such as the concurrent control between data and metadata are not fully designed and implemented. In CEFT [6], [10], [13], [17], which is an extension of PVFS to incorporate a RAID-10-style fault tolerance and parallel I/O scheduling, the MS synchronizes concurrent updates, which can limit the overall throughput under the workload of intensive concurrent metadata updates. In Lustre [1], some low-level metadata management tasks are offloaded from the MS to object storage devices, and ongoing efforts are being made to decentralize metadata management to further improve the scalability.…”

Section: Related Work and Comparison Of Decentralization Schemesmentioning

confidence: 99%

“…To divert the high volume of user data traffic to bypass any single centralized component, the functions of data and metadata managements are usually decomposed, and metadata is stored separately on different nodes away from user data. Although previous work on cluster-based storage mainly focuses on optimizing the scalability and efficiency of user data accesses by using a RAID-style striping [3], [10], caching [11], scheduling [12], [13], and networking [14], little attention has been drawn to the scalability of metadata management.…”

Section: Introductionmentioning

confidence: 99%

HBA: Distributed Metadata Management for Large Cluster-Based Storage Systems

Zhu

Jiang

Wang

et al. 2008

IEEE Trans. Parallel Distrib. Syst.

View full text Add to dashboard Cite

Abstract-An efficient and distributed scheme for file mapping or file lookup is critical in decentralizing metadata management within a group of metadata servers. This paper presents a novel technique called Hierarchical Bloom Filter Arrays (HBA) to map filenames to the metadata servers holding their metadata. Two levels of probabilistic arrays, namely, the Bloom filter arrays with different levels of accuracies, are used on each metadata server. One array, with lower accuracy and representing the distribution of the entire metadata, trades accuracy for significantly reduced memory overhead, whereas the other array, with higher accuracy, caches partial distribution information and exploits the temporal locality of file access patterns. Both arrays are replicated to all metadata servers to support fast local lookups. We evaluate HBA through extensive trace-driven simulations and implementation in Linux. Simulation results show our HBA design to be highly effective and efficient in improving the performance and scalability of file systems in clusters with 1,000 to 10,000 nodes (or superclusters) and with the amount of data in the petabyte scale or higher. Our implementation indicates that HBA can reduce the metadata operation time of a single-metadata-server architecture by a factor of up to 43.9 when the system is configured with 16 metadata servers.Index Terms-Distributed file systems, file system management, metadata management, Bloom filter.

show abstract

“…Each block (approximately 64 megabytes (MB)) is then stored in multiple different storage nodes to enhance concurrency and system performance [ 1 ]. Moreover, a number of other similar systems, such as RAID (Redundant Array of Independent Disks) systems [ 2 ] and geospatial information systems (GISs) [ 3 ], have been developed, all of which use declustering technologies for the distributed storage of large files.…”

Section: Introductionmentioning

confidence: 99%

Distributed Storage Algorithm for Geospatial Image Data Based on Data Access Patterns

Pan

Wang

et al. 2015

PLoS ONE

View full text Add to dashboard Cite

Declustering techniques are widely used in distributed environments to reduce query response time through parallel I/O by splitting large files into several small blocks and then distributing those blocks among multiple storage nodes. Unfortunately, however, many small geospatial image data files cannot be further split for distributed storage. In this paper, we propose a complete theoretical system for the distributed storage of small geospatial image data files based on mining the access patterns of geospatial image data using their historical access log information. First, an algorithm is developed to construct an access correlation matrix based on the analysis of the log information, which reveals the patterns of access to the geospatial image data. Then, a practical heuristic algorithm is developed to determine a reasonable solution based on the access correlation matrix. Finally, a number of comparative experiments are presented, demonstrating that our algorithm displays a higher total parallel access probability than those of other algorithms by approximately 10–15% and that the performance can be further improved by more than 20% by simultaneously applying a copy storage strategy. These experiments show that the algorithm can be applied in distributed environments to help realize parallel I/O and thereby improve system performance.

show abstract

Exploiting redundancy to boost performance in a RAID-10 style cluster-based file system

Cited by 4 publications

References 23 publications

CEFT: A cost-effective, fault-tolerant parallel virtual file system

CEFT: A cost-effective, fault-tolerant parallel virtual file system

HBA: Distributed Metadata Management for Large Cluster-Based Storage Systems

Distributed Storage Algorithm for Geospatial Image Data Based on Data Access Patterns

Contact Info

Product

Resources

About