zCeph: Design and implementation of a ZNS-friendly distributed file system

IF 6.2 2区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Jin Yong Ha , Yongseok Son
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Abstract

This article presents zCeph, a ZNS-friendly distributed file system designed to efficiently utilize zoned namespace (ZNS) SSDs. Specifically, we first propose MZAllocator which enables multiple zones to be utilized simultaneously to maximize the performance of ZNS SSDs. Second, we adopt an append command to eliminate the need for synchronization in write ordering within distributed storage systems to improve scalability. Third, we present zBlueFS, a ZNS-aware user-level file system based on BlueFS to update the metadata on the ZNS SSD without a conventional SSD. Finally, we propose a delta write technique, DeltaWriter, which writes only a modified part of the metadata (i.e., onode) to reduce read–modify–write overhead whenever the metadata are updated. We implement zCeph with four techniques based on Ceph, an open-source distributed file system. Further, we evaluate zCeph on a pair of 48-core machines with ZNS SSDs using micro and macro benchmarks, and the results reveal that zCeph improves performance by up to 4.2× and 8.8× compared with Ceph, respectively.

Abstract Image

zCeph:一个zns友好的分布式文件系统的设计和实现
本文介绍了zCeph,这是一个ZNS友好的分布式文件系统,旨在有效地利用分区命名空间(ZNS) ssd。具体来说,我们首先提出了MZAllocator,它可以同时利用多个区域,以最大限度地提高ZNS ssd的性能。其次,我们采用了一个append命令来消除分布式存储系统中写顺序同步的需要,以提高可伸缩性。第三,我们提出了zBlueFS,这是一个基于BlueFS的ZNS感知用户级文件系统,可以在没有传统SSD的情况下更新ZNS SSD上的元数据。最后,我们提出了一种增量写入技术,DeltaWriter,它只写入元数据的修改部分(即onode),以减少元数据更新时的读-修改-写开销。我们使用基于Ceph的四种技术来实现zCeph, Ceph是一个开源的分布式文件系统。此外,我们在一对使用ZNS ssd的48核机器上使用微观和宏观基准测试来评估zCeph,结果表明zCeph与Ceph相比分别提高了4.2倍和8.8倍的性能。
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来源期刊
CiteScore
19.90
自引率
2.70%
发文量
376
审稿时长
10.6 months
期刊介绍: Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications. Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration. Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.
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