Asynchronous object storage with QoS for scientific and commercial big data

Michael J. Brim, D. Dillow, S. Oral, B. Settlemyer, Feiyi Wang
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引用次数: 16

Abstract

This paper presents our design for an asynchronous object storage system intended for use in scientific and commercial big data workloads. Use cases from the target workload domains are used to motivate the key abstractions used in the application programming interface (API). The architecture of the Scalable Object Store (SOS), a prototype object storage system that supports the API's facilities, is presented. The SOS serves as a vehicle for future research into scalable and resilient big data object storage. We briefly review our research into providing efficient storage servers capable of providing quality of service (QoS) contracts relevant for big data use cases.
面向科学大数据和商业大数据的具有QoS的异步对象存储
本文介绍了我们设计的异步对象存储系统,用于科学和商业大数据工作负载。来自目标工作负载域的用例用于激励应用程序编程接口(API)中使用的关键抽象。给出了可扩展对象存储(SOS)的体系结构,这是一个支持API功能的原型对象存储系统。SOS可以作为未来研究可扩展和弹性大数据对象存储的工具。我们简要回顾了我们对提供高效存储服务器的研究,这些服务器能够提供与大数据用例相关的服务质量(QoS)合同。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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