AutoScaling of VM in Private And Public Cloud Environment with Debt Assessment

S. Santhosh, A. Binu
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引用次数: 1

Abstract

Cloud computing is an enchanting technology for the allocation of resources on-demand. The cloud Systems mostly hinges upon Virtualization techniques for the resource allocation purposes. All the Cloud Services that service providers put forward are chargeable and are charging the users depending on demand. So its important for them to improve the scalability factor to provide a superlative service to the users. As a solution, recently the providers began to use an auto scaling mechanism which can scale the resources according to the need of them. Auto Scaling mechanism on Virtual machines will impart a streamlined use of cloud resources. It is considered as an effective Resource management technique that utilize data center in structured manner although, the already existing scaling methods just take into account CPU utilization only. Hence it is needed to consider an Auto Scaling method that guarantees the execution of applications within the deadline. So here we concentrate on an auto scaling method that handles Bag-of-Tasks jobs in Private and Public cloud environment. The results of Simulation shows how effectively the resources are allocated considering the deadline as parameter.
私有云和公共云环境中虚拟机的自动扩展与债务评估
云计算是一种按需分配资源的迷人技术。云系统主要依靠虚拟化技术来实现资源分配。服务提供商提供的所有云服务都是收费的,并根据需求向用户收费。因此,提高可扩展性系数,为用户提供一流的服务对他们来说非常重要。作为一种解决方案,最近提供商开始使用一种自动扩展机制,可以根据需要扩展资源。虚拟机上的自动伸缩机制将使云资源的使用更加流畅。它被认为是一种有效的资源管理技术,以结构化的方式利用数据中心,尽管现有的扩展方法只考虑CPU利用率。因此,需要考虑一种自动缩放方法,以保证在截止日期内执行应用程序。因此,在这里,我们专注于一种自动缩放方法,该方法可以处理私有云和公共云环境中的任务袋作业。仿真结果表明,以最后期限为参数,资源分配是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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