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Formal Quality of Service assurances, ranking and verification of cloud deployment options with a probabilistic model checking method

机译:正式的服务质量保证,使用概率模型检查方法对云部署选项进行排名和验证

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摘要

Context: Existing software workbenches allow for the deployment of cloud applications across a variety of Infrastructure-as-a-Service (IaaS) providers. The expected workload, Quality of Service (QoS) and Non-Functional Requirements (NFRs) must be considered before an appropriate infrastructure is selected. However, this decision-making process is complex and time-consuming. Moreover, the software engineer needs assurances that the selected infrastructure will lead to an adequate QoS of the application.Objective: The goal is to develop a new method for selection of an optimal cloud deployment option, that is, an infrastructure and configuration for deployment and to verify that all hard and as many soft QoS requirements as possible will be met at runtime.Method: A new Formal QoS Assurances Method (FoQoSAM), which relies on stochastic Markov models is introduced to facilitate an automated decision-making process. For a given workload, it uses QoS monitoring data and a user-related metric in order to automatically generate a probabilistic model. The probabilistic model takes the form of a finite automaton. It is further used to produce a rank list of cloud deployment options. As a result, any of the cloud deployment options can be verified by applying a probabilistic model checking approach.Results: Testing was performed by ranking deployment options for two cloud applications, File Upload and Video-conferencing. The FoQoSAM method was compared to a baseline Analytic Hierarchy Process (AHP). The results show that the first ranked cloud deployment options satisfy all hard and at least one of the soft requirements for both methods, however, the FoQoSAM method always satisfies at least an additional QoS requirement compared to the baseline AHP method.Conclusions: The proposed new FoQoSAM method is appropriate and can be used in decision-making when ranking and verifying cloud deployment options. Due to its practical utility it was integrated into the SWITCH workbench.
机译:上下文:现有的软件工作台允许跨各种基础架构即服务(IaaS)提供程序部署云应用程序。在选择适当的基础结构之前,必须考虑预期的工作负载,服务质量(QoS)和非功能需求(NFR)。但是,该决策过程复杂且耗时。此外,软件工程师还需要确保所选的基础架构能够带来足够的应用程序QoS。目的:目标是开发一种用于选择最佳云部署选项的新方法,即用于部署和部署的基础架构和配置。方法:采用一种新的基于随机马尔可夫模型的正式QoS保证方法(FoQoSAM),以促进自动化的决策过程。对于给定的工作负载,它使用QoS监视数据和与用户相关的指标来自动生成概率模型。概率模型采用有限自动机的形式。它进一步用于生成云部署选项的等级列表。结果,可以通过应用概率模型检查方法来验证任何云部署选项。结果:通过对两个云应用程序(文件上传和视频会议)的部署选项进行排名来进行测试。将FoQoSAM方法与基线分析层次过程(AHP)进行了比较。结果表明,排名第一的云部署选项可以满足这两种方法的所有硬性要求和至少一个软性要求,但是与基准AHP方法相比,FoQoSAM方法始终至少满足额外的QoS要求。 FoQoSAM方法是适当的,可用于在对云部署选项进行排名和验证时进行决策。由于其实用性,它已集成到SWITCH工作台中。

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