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CSR: Small:Taming Small Data Writes to Block Storage Devices for Higher I/O Efficiency

CSR: Small:Taming Small Data Writes to Block Storage Devices for Higher I/O Efficiency
CSR:小:驯服小数据写入块存储设备以提高 I/O 效率
批准号:
1527076
负责人:
Song Jiang
金额:
$50.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-10-01 至 2016-11-30

项目摘要

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中文摘要
翻译
存储系统是大型数据中心中最关键的基础设施之一。很多工作都是为了允许数据在存储设备上可伸缩和有效访问。大数据对存储系统提出了巨大的挑战,而小数据对访问效率提出了同样严峻的挑战,需要创新的研究解决方案。几乎所有的存储设备都使用块接口,这种接口很难被替代。访问小数据可能会浪费设备带宽,并显著降低输入/输出(I/O)效率,从而导致硬件和能源成本大幅提高,并降低最终用户的服务质量。该研究项目基于在各种应用场景中显示一致有效性的初步结果,将采用使用数据压缩技术的破坏性过程来隐藏或删除小数据写入。由于对即时数据持久性的需求,小数据的写入仍然是块设备的致命弱点。在I/O堆栈中有多个软件层与块接口交互,在这些层中,小数据写入可能会造成很大的性能损失。这些层包括虚拟块设备、I/O调度器和文件系统。提议的解决方案利用了数据压缩技术,而不是依赖于特殊的硬件支持或要求更改接口。它允许小数据有效地通过几乎所有存储设备采用的严格但必要的块接口,以提供持久性和原子性,而无需额外的块写入和刷新操作。所提出的策略将在很大程度上有效地解决小写入问题,并对行业产生深远的影响。预期的软件构件将被构建到Linux和Ext3之类的文件系统中,并向社区开放以供共享。
英文摘要
Storage systems are one of the most critical infrastructures in large-scale data centers. Much effort has been directed to allow data to be scalable and efficiently accessed on storage devices. While big data poses big challenges to storage systems, small data presents equally serious access efficiency challenges and begs for innovative research solutions. Almost all storage devices use block interface, which can hardly be replaced. Accessing small data potentially results in wasted device bandwidth and significantly reduced input/output (I/O) efficiency which leads to substantially higher hardware and energy costs and compromised service quality to end users. This research project, based on preliminary results that have shown consistent effectiveness in various application scenarios, will employ a disruptive process using data compression techniques to hide or remove small data writes. Because of demand on immediate data persistency, writes of the small-data continue to be the Achilles' heel of block devices. There are multiple software layers across the I/O stack interacting with the block interface, where small-data writes can inflict a substantial performance penalty. The layers include virtual block devices, I/O schedulers, and file systems. Instead of relying on special hardware support or demanding interface changes, the proposed solution leverages data compression techniques. It allows small data to efficiently pass through the rigid but necessary block interface adopted by almost all storage devices to provide persistency and atomicity without extra block write and flush operations. The proposed strategy would effectively address the issue with small writes to a great extent and profoundly benefit the industry. The expected software artifacts will be built into Linux and file systems such as Ext3, and be open to the community for sharing.
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