A CBR MAC/FAC Approach for Cloud Management

Eric Kübler, Miriam Herold, Mirjam Minor
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Abstract

In modern working world, efficiency is important. This includes the execution of workflows. Cloud computing offers is costumers, pay as you go pricing models which can be used to improve the cost efficiency of workflows execution. To benefit form this pricing model, a smart cloud management concept to assign tasks to cloud resources is required. Simple solutions struggle with over-, and under-provisioning problems or lack the needed flexibility. In this paper we present our CBR approach with MAC/FAC similarity function and experiments for task placements in cloud computing. Therefore we implemented a prototype and compared the results with the results of human experts.
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云管理的CBR MAC/FAC方法
在现代工作世界中,效率是重要的。这包括工作流的执行。云计算为客户提供了按需付费的定价模型,可以用来提高工作流执行的成本效率。为了从这种定价模式中获益,需要一种智能云管理概念来为云资源分配任务。简单的解决方案会遇到供应过剩和供应不足的问题,或者缺乏所需的灵活性。在本文中,我们提出了基于MAC/FAC相似函数的CBR方法,并对云计算中的任务放置进行了实验。因此,我们实现了一个原型,并将结果与人类专家的结果进行了比较。
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