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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引用次数: 0

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.

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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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