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Modeling and Evaluating Cross-layer Elasticity Strategies in Cloud Systems

机译:云系统中跨层弹性策略的建模和评估

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Clouds are complex systems that provide computing resources in an elastic way. Elasticity property allows their adaptation to input workload by (de) provisioning resources as the demand rises and drops. However, due to the numerous overlapping factors that impact their elasticity and the unpredictable nature of the workload, providing accurate action plans to manage cloud systems' elastic adaptations is a particularly challenging task. In this paper, we propose an approach based on Bigraphical Reactive Systems (BRS) to model cloud structures and their elastic behavior. We design elasticity strategies that operate at service and infrastructure cloud levels to manage the elastic adaptations. Besides, we provide a Maude encoding to permit generic executability and formal verification of the elastic behaviors. One step ahead, we show how the strategies can be combined at both levels to provide different high-level elastic behaviors. Finally, we evaluate the different cross-layer combinations using Queuing Theory.
机译:云是复杂的系统,以弹性方式提供计算资源。弹性属性允许它们随着需求的上升和下降通过(取消)供应资源来适应输入的工作负载。但是,由于许多重叠的因素会影响其弹性以及工作负载的不可预测性,因此提供准确的行动计划来管理云系统的弹性适应是一项特别具有挑战性的任务。在本文中,我们提出了一种基于生物反应系统(BRS)的方法来对云结构及其弹性行为进行建模。我们设计在服务和基础架构云级别上运行的弹性策略,以管理弹性适应。此外,我们提供了Maude编码,以允许通用可执行性和弹性行为的形式验证。向前迈出的第一步,我们展示了如何在两个级别上组合策略以提供不同的高级弹性行为。最后,我们使用排队论评估不同的跨层组合。

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