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Understanding Data Characteristics and Access Patterns in a Cloud Storage System

机译:了解云存储系统中的数据特征和访问模式

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Understanding the inherent system characteristics is crucial to the design and optimization of cloud storage system, and few studies have systematically investigated its data characteristics and access patterns. This paper presents an analysis of file system snapshot and five-month access trace of a campus cloud storage system that has been deployed on Tsinghua campus for three years. The system provides online storage and data sharing services for more than 19,000 students and 500 student groups. We report several data characteristics including file size and file type, as well as some access patterns, including read/write ratio, read-write dependency and daily traffic. We find that there are many differences between cloud storage system and traditional file systems: our cloud storage system has larger file sizes, lower read/write ratio, and smaller set of active files than those of a typical traditional file system. With a trace-driven simulation, we find that the cache efficiency can be improved by 5 times using the guidance from our observations.
机译:理解系统固有的特性对于云存储系统的设计和优化至关重要,很少有研究系统地研究其数据特性和访问模式。本文对已经在清华大学校园部署了三年的校园云存储系统的文件系统快照和五个月的访问轨迹进行了分析。该系统为19,000多名学生和500个学生团体提供在线存储和数据共享服务。我们报告了一些数据特征,包括文件大小和文件类型,以及一些访问模式,包括读写比,读写依存关系和日常流量。我们发现云存储系统与传统文件系统之间存在许多差异:与典型的传统文件系统相比,我们的云存储系统具有更大的文件大小,更低的读写比和更少的活动文件集。通过跟踪驱动的仿真,我们发现,根据我们的观察结果,缓存效率可以提高5倍。

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