Understanding I/O performance behaviors of cloud storage from a client's perspective

Binbing Hou, Feng Chen, Zhonghong Ou, Ren Wang, M. Mesnier
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引用次数: 20

Abstract

Cloud storage has gained increasing popularity in the past few years. In cloud storage, data is stored in the service provider's data centers, and users access data via the network. For such a new storage model, our prior wisdom about conventional storage may not remain valid nor applicable to the emerging cloud storage. In this paper, we present a comprehensive study and attempt to gain insight into the unique characteristics of cloud storage, primarily from the client's perspective. Through extensive experiments and quantitative analysis, we have acquired several interesting, and in some cases unexpected, findings. (1) Parallelizing I/Os and increasing request sizes are keys to improving the performance, but optimal bandwidth may only be achieved with a proper combination of parallelism and request size. (2) Client capabilities, including CPU, memory, and storage, play an unexpectedly important role in determining the achievable performance. (3) A geographically long distance affects client-perceived performance but does not always result in lower bandwidth and longer latency. Based on our experimental studies, we further present a case study on appropriate chunking and parallelization in a cloud storage client. Our studies show that specific attention should be paid to fully exploiting the capabilities of clients and the great potential of cloud storage services.
从客户端的角度理解云存储的I/O性能行为
云存储在过去几年中越来越受欢迎。在云存储中,数据存储在服务提供商的数据中心,用户通过网络访问数据。对于这样一种新的存储模式,我们之前关于传统存储的智慧可能不再有效,也不适用于新兴的云存储。在本文中,我们主要从客户的角度进行了全面的研究,并试图深入了解云存储的独特特征。通过广泛的实验和定量分析,我们获得了一些有趣的,有时是意想不到的发现。(1)并行I/ o和增加请求大小是提高性能的关键,但最佳带宽可能只有通过并行性和请求大小的适当组合才能实现。(2)客户端能力,包括CPU、内存和存储,在决定可实现的性能方面起着意想不到的重要作用。(3)地理上的长距离影响客户端感知的性能,但并不总是导致较低的带宽和较长的延迟。基于我们的实验研究,我们进一步提出了在云存储客户端中适当分块和并行化的案例研究。我们的研究表明,应特别注意充分利用客户的能力和云存储服务的巨大潜力。
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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