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Minimizing Resource Rent Loss while Maximizing User Availability in Cloud Applications through Online Switching of the Scaling Method

机译:通过在线切换来最大限度地减少资源租金损失,同时通过缩放方法的在线切换将用户可用性最大化在云应用程序中

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Clouds offer access to virtually unlimited resources. Applications requiring a variable number of resources (i.e., elastic) are hence ideal for such a scenario. As cloud resources are usually paid by the hour applications need efficient ways of predicting their requirements in order to reduce costs. In addition we need to maximize user satisfaction through high application availability. Finding the best balance between them is a crucial task. In this paper we consider the case of commercial web applications and focus on the hit rate as scaling factor. Since it is known that no scaling algorithm can have a definite edge over the rest we propose three strategies for online scaling strategy switching. The first one chooses at each step always the best strategy. The second one focuses on analysing the probability distribution of the historic hit rate and determining the best scaling method for it. Finally, the third one relies on changing the method without needing to know the distribution through random choices. Results show that given the fluctuations and uncertainty of cloud environments and user behaviour the most suited method for online selection of the scaling strategy is the first one based on the best strategy.
机译:云提供几乎无限的资源的访问。因此,需要变量资源(即弹性)的应用是理想的这种情况。随着云资源通常由小时应用程序支付,需要有效地预测其要求以降低成本。此外,我们需要通过高应用可用性最大限度地提高用户满意度。找到它们之间的最佳平衡是一个重要的任务。在本文中,我们考虑了商业网络应用的情况,并将命中率关注为缩放因子。由于已知没有缩放算法可以在其余部分中具有明确的边缘,我们提出了三个在线缩放策略切换的策略。第一个在每个步骤中选择始终是最好的策略。第二个专注于分析历史击中率的概率分布,并确定其最佳缩放方法。最后,第三个依赖于改变方法,而无需通过随机选择知道分发。结果表明,鉴于云环境和用户行为的波动和不确定性,缩放策略的最适合在线选择的在线选择是基于最佳策略的第一个。

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