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Dynamic Scalability Model for Containerized Cloud Services

机译:集装箱云服务的动态可伸缩性模型

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Cloud computing has become an important research area in large-scale computing systems and is being employed by many organizations in government, businesses, and industry. Schemes and appropriate models for dynamic resources provisioning in the cloud environment have been extensively studied. To date, the research literature is lacking schemes and models that offer dynamic scalability in which Quality of Service (QoS) and high performance are provided to customers with the usage of the least number of cloud resources, especially for containerized services hosted on the cloud. With dynamic scalability, cloud computing can offer on-demand, timely, and dynamically adjustable computing resources to services hosted on the cloud. This paper presents a dynamic scaling model based on queueing theory to scale containers virtual resources and satisfy the customer Service Level Agreements (SLA) while guarding costs of scaling very low. The aim is to improve the virtual computing resources utilization and satisfy SLA constraints in terms of CPU utilization, system response time, system drop rate, system number of tasks, and system throughput. Simulation results are provided using Java Modelling Tools simulation tool, which shows that our proposed model can determine under any offered workload the needed containers instances to satisfy the required QoS parameters.
机译:云计算已成为大型计算系统中的一个重要研究领域,并受到政府,企业和行业的许多组织所雇用的。已经广泛研究了云环境中动态资源供应的方案和适当模型。迄今为止,研究文献缺乏提供动态可扩展性的计划和模型,其中提供服务质量(QoS)和高性能,以满足云资源数量最少的云资源,尤其是在云上托管的集装箱服务。具有动态可扩展性,云计算可以为云上托管的服务提供按需,及时和动态可调节的计算资源。本文介绍了一种基于排队理论的动态缩放模型,以规模容器虚拟资源,满足客户服务级别协议(SLA),同时保护非常低的缩放成本。目的是在CPU利用率,系统响应时间,系统跌幅,系统任务数和系统吞吐量方面提高虚拟计算资源利用率和满足SLA约束。使用Java建模工具仿真工具提供了仿真结果,这表明我们所提出的模型可以在任何提供的工作负载下确定所需的容器实例来满足所需的QoS参数。

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