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A multi-channel architecture for metadata management in cloud storage systems by binding CPU-cores to disks

机译:通过将CPU内核绑定到磁盘来在云存储系统中进行元数据管理的多通道架构

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Metadata operations have become dominant file operations in the storage systems. In the scenarios of read-more and write-less of massive small files, the current distributed file systems suffer from the unsatisfying performance and scalability of metadata service because of random disk I/O during metadata operations. In this paper, a highly efficient metadata management architecture for cloud storage systems is proposed. The cluster design significantly improves the scalability of the system. A concept of the disk I/O channel is introduced, which is an independent data storage pipe by binding an independent CPU-core to each physical disk. In addition, a multi-channel fast key-value storage engine is proposed to provide the extremely efficient performance for the underlying storage service, which takes full advantages of multi-core processors and parallel disks I/O. Besides, a new dynamic load-balancing strategy is proposed to reduce load thrashing and improve the precision of rebalancing among the clusters. Performance measurements under a variety of benchmarks show that the metadata management is capable of handling the massive small files storage and the performance is improved significantly compared to the existing solutions. Copyright © 2016 John Wiley & Sons, Ltd.
机译:元数据操作已成为存储系统中的主要文件操作。在读取和写入大量小文件的情况下,由于元数据操作期间的随机磁盘I / O,当前的分布式文件系统的元数据服务的性能和可伸缩性令人不满意。本文提出了一种用于云存储系统的高效元数据管理架构。集群设计显着提高了系统的可伸缩性。引入了磁盘I / O通道的概念,它是通过将独立的CPU内核绑定到每个物理磁盘而成为独立的数据存储管道。此外,提出了一种多通道快速键值存储引擎,以为基础存储服务提供极其高效的性能,该引擎充分利用了多核处理器和并行磁盘I / O的优势。此外,提出了一种新的动态负载均衡策略,以减少负载抖动并提高集群之间重新均衡的精度。在各种基准下的性能测量表明,元数据管理能够处理大量的小文件存储,并且与现有解决方案相比,性能得到了显着改善。版权所有©2016 John Wiley&Sons,Ltd.

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