数据密集型云中的资源管理:机遇与挑战

David E. Irwin, P. Shenoy, E. Cecchet, M. Zink
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引用次数: 21

摘要

今天的云计算平台在运行具有时变或一次性需求的计算绑定应用程序方面取得了很大成功。在本文中,我们将论证云范式也非常适合处理数据密集型应用程序,其特点是处理和存储高带宽传感器或流应用程序产生的数据。对于许多这样的应用程序,数据速率和处理需求会随着时间的推移而变化,这使得按需云模式很好地满足了它们的需求。然而,今天的云平台需要不断发展,以满足数据密集型应用程序的存储、通信和处理需求。我们提出了一个正在进行的GENI项目,将高带宽雷达传感器网络与云中的计算和存储资源连接起来,并使用这个例子来强调设计端到端数据密集型云系统的机遇和挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Resource management in data-intensive clouds: Opportunities and challenges
Today's cloud computing platforms have seen much success in running compute-bound applications with time-varying or one-time needs. In this position paper, we will argue that the cloud paradigm is also well suited for handling data-intensive applications, characterized by the processing and storage of data produced by high-bandwidth sensors or streaming applications. The data rates and the processing demands vary over time for many such applications, making the on-demand cloud paradigm a good match for their needs. However, today's cloud platforms need to evolve to meet the storage, communication, and processing demands of data-intensive applications. We present an ongoing GENI project to connect high-bandwidth radar sensor networks with computational and storage resources in the cloud and use this example to highlight the opportunities and challenges in designing end-to-end data-intensive cloud systems.
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