Auto-scalability is a common approach for management of cloud applications where resources are provisioned and de-provisioned on demand. Because of its automatic nature, auto-scaling can be exploited for various reasons that can hugely reduce the overall profit. Therefore, it becomes vital to consider the trade-off between the added revenue as a result of auto-scaling and its corresponding cost. To this end, we propose a novel autonomic solution to the management of cloud Web applications whose goal is to optimize the profit. At the core of the solution, there is an optimization module that considers revenue model as well as cost model and uses a number of run-time performance models to derive the best course of action if there is a need for adaptation. Using software defined features that include compute and network programmability, our proposed solution helps applications to optimize their resource allocation to best meet their business requirements. Our experiment results on a hybrid cloud validate the applicability of the proposed solution and demonstrate that it can increase the profit substantially higher compared to a number of baseline approaches.

中文翻译：

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软件定义基础设施上 Web 应用程序的自适应负载管理

自动可扩展性是管理云应用程序的常用方法，其中资源按需供应和取消供应。由于其自动性质，可以出于各种原因利用自动缩放，这会大大降低整体利润。因此，考虑因自动缩放而增加的收入与其相应成本之间的权衡变得至关重要。为此，我们提出了一种新颖的自主解决方案来管理云 Web 应用程序，其目标是优化利润。该解决方案的核心是一个优化模块，该模块考虑收入模型和成本模型，并在需要调整时使用多个运行时性能模型得出最佳行动方案。使用软件定义的功能，包括计算和网络可编程性，我们提出的解决方案可帮助应用程序优化其资源分配，以最好地满足其业务需求。我们在混合云上的实验结果验证了所提出解决方案的适用性，并证明与许多基线方法相比，它可以显着提高利润。