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Kriging-Based Self-Adaptive Cloud Controllers

机译:基于Kriging的自适应云控制器

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摘要

Cloud technology is rapidly substituting classic computing solutions, and challenges the community with new problems. In this paper we focus on controllers for cloud application elasticity, and propose a novel solution for self-adaptive cloud controllers based on Kriging models. Cloud controllers are application specific schedulers that allocate resources to applications running in the cloud, aiming to meet the quality of service requirements while optimizing the execution costs. General-purpose cloud resource schedulers provide sub-optimal solutions to the problem with respect to application-specific solutions that we call cloud controllers. In this paper we discuss a general way to design self-adaptive cloud controllers based on Kriging models. We present Kriging models, and show how they can be used for building efficient controllers thanks to their unique characteristics. We report experimental data that confirm the suitability of Kriging models to support efficient cloud control and open the way to the development of a new generation of cloud controllers.
机译:云技术正在迅速取代传统的计算解决方案,并向社区提出了新问题。在本文中,我们将重点放在用于云应用弹性的控制器上,并基于Kriging模型为自适应云控制器提出一种新的解决方案。云控制器是特定于应用程序的调度程序,可将资源分配给在云中运行的应用程序,旨在满足服务质量要求,同时优化执行成本。相对于我们称为云控制器的特定于应用程序的解决方案,通用云资源调度程序为该问题提供了次优解决方案。在本文中,我们讨论了一种基于Kriging模型设计自适应云控制器的一般方法。我们介绍了Kriging模型,并展示了其独特的特性如何将其用于构建高效的控制器。我们报告的实验数据证实了Kriging模型是否适合支持有效的云控制,并为开发新一代的云控制器开辟了道路。

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