Provisioning, Placement and Pipelining Strategies for Data-Intensive Applications in Cloud Environments

D. Ghoshal, L. Ramakrishnan
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引用次数: 8

Abstract

Clouds are increasingly being used for running data-intensive scientific applications. Data-intensive science applications need performance, scalability and reliability. However, these can be hard to achieve in cloud environments. Intelligent strategies are required to obtain better performance, scalability and reliability on cloud platforms. In this paper, we propose a set of pipelining strategies to effectively utilize provisioned cloud resources. Our experiments on the ExoGENI cloud testbed demonstrates the effectiveness of our approach in increasing performance and reducing failures.
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云环境中数据密集型应用程序的配置、放置和流水线策略
云越来越多地被用于运行数据密集型科学应用程序。数据密集型科学应用需要性能、可扩展性和可靠性。然而,这些在云环境中很难实现。为了在云平台上获得更好的性能、可扩展性和可靠性,需要智能策略。在本文中,我们提出了一套流水线策略来有效地利用所提供的云资源。我们在ExoGENI云测试平台上的实验证明了我们的方法在提高性能和减少故障方面的有效性。
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