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PEESOS-Cloud: A Workload-Aware Architecture for Performance Evaluation in Service-Oriented Systems

机译:PEESOS-Cloud:用于面向服务的系统中的性能评估的工作负载感知架构

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It is a challenging task to ensure quality in service-oriented systems deployed in cloud computing owing to the dynamicity of its environment. Many approaches have been adopted to identify and evaluate bottlenecks and problems in performance. The most common scenario consists of distributed systems that use a workload capable of enabling clients to exploit the target system in different operational conditions. However, one requirement that tends to be overlooked is to determine how the workload is executed, as software and hardware faults can lead to its mischaracterization. In this paper, a number of problems in the workload generation have been identified and summarized. A new architecture, called PEESOS-Cloud, is proposed which allows these services to be evaluated as well as to improve the ability of the workload so that it conforms with its described characteristics. Experiments in a cloud environment were conducted to show how PEESOS-Cloud works and validate its capabilities. Our experiment also showed that the mischaracterization of the workload leads to poor results, whereas an workload-aware implementation leads to a better performance evaluation.
机译:由于其环境的动态性,确保部署在云计算中的面向服务的系统的质量是一项艰巨的任务。已经采用了许多方法来识别和评估性能方面的瓶颈和问题。最常见的场景包括分布式系统,这些系统使用的工作负载能够使客户端在不同的操作条件下利用目标系统。但是,一个容易被忽略的要求是确定工作负载的执行方式,因为软件和硬件故障可能导致其错误表征。在本文中,已经确定并总结了工作负载生成中的许多问题。提出了一种称为PEESOS-Cloud的新体系结构,该体系结构可以评估这些服务并提高工作负载的能力,使其符合其描述的特征。在云环境中进行了实验,以显示PEESOS-Cloud如何工作并验证其功能。我们的实验还表明,工作负载的错误表征会导致较差的结果,而工作负载感知的实现会导致更好的性能评估。

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