上下文感知云拓扑优化与仿真的CACTOS远景

Per-Olov Östberg, Henning Groenda, S. Wesner, James Byrne, Dimitrios S. Nikolopoulos, Craig Sheridan, Jakub Krzywda, A. Ali-Eldin, Johan Tordsson, E. Elmroth, Christian Stier, K. Krogmann, Jörg Domaschka, Christopher B. Hauser, P. J. Byrne, Sergej Svorobej, B. McCollum, Zafeirios C. Papazachos, D. Whigham, S. Ruth, Dragana Paurevic
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引用次数: 30

摘要

硬件开发的最新进展,加上云计算的迅速采用和广泛适用性,在数据中心中引入了广泛的异构性,使云应用程序和数据中心资源的管理大大复杂化。本文介绍了CACTOS实现云基础设施自动化和优化的方法,该方法通过对应用程序行为的深入分析与商业云提供商的见解相结合来解决异构问题。该方法的目的有三个:为应用程序和数据中心资源建模,为规划和操作模拟应用程序和资源,并以自主的方式优化应用程序部署和资源使用。该方法基于来自业务分析、企业应用程序和科学计算领域的案例研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The CACTOS Vision of Context-Aware Cloud Topology Optimization and Simulation
Recent advances in hardware development coupled with the rapid adoption and broad applicability of cloud computing have introduced widespread heterogeneity in data centers, significantly complicating the management of cloud applications and data center resources. This paper presents the CACTOS approach to cloud infrastructure automation and optimization, which addresses heterogeneity through a combination of in-depth analysis of application behavior with insights from commercial cloud providers. The aim of the approach is threefold: to model applications and data center resources, to simulate applications and resources for planning and operation, and to optimize application deployment and resource use in an autonomic manner. The approach is based on case studies from the areas of business analytics, enterprise applications, and scientific computing.
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