Integrated and autonomic cloud resource scaling

M. Hasan, Edgar Magaña, A. Clemm, L. Tucker, Sree Lakshmi D. Gudreddi
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引用次数: 123

Abstract

A Cloud is a very dynamic environment where resources offered by a Cloud Service Provider (CSP), out of one or more Cloud Data Centers (DCs) are acquired or released (by an enterprise (tenant) on-demand and at any scale. Typically a tenant will use Cloud service interfaces to acquire or release resources directly. This process can be automated by a CSP by providing auto-scaling capability where a tenant sets policies indicating under what condition resources should be auto-scaled. This is specially needed in a Cloud environment because of the huge scale at which a Cloud operates. Typical solutions are naïve causing spurious auto-scaling decisions. For example, they are based on only thresholding triggers and the thresholding mechanisms themselves are not Cloud-ready. In a Cloud, resources from three separate domains, compute, storage and network, are acquired or released on-demand. But in typical solutions resources from these three domains are not auto-scaled in an integrated fashion. Integrated auto-scaling prevents further spurious scaling and reduces the number of auto-scaling systems to be supported in a Cloud management system. In addition, network resources typically are not auto-scaled. In this paper we describe a Cloud resource auto-scaling system that addresses and overcomes above limitations.
集成和自主的云资源扩展
云是一个非常动态的环境,其中云服务提供商(CSP)从一个或多个云数据中心(dc)中提供的资源可以按需(由企业(租户))以任何规模获取或释放。通常,租户将使用云服务接口直接获取或释放资源。CSP可以通过提供自动扩展功能来自动化此过程,其中租户设置策略,指示在什么条件下应该自动扩展资源。这在云环境中是特别需要的,因为云操作的规模非常大。典型的解决方案是naïve,导致错误的自动缩放决策。例如,它们仅基于阈值触发器,而阈值机制本身不支持云。在云计算中,来自三个独立领域(计算、存储和网络)的资源是按需获取或释放的。但是在典型的解决方案中,这三个领域的资源不能以集成的方式自动扩展。集成的自动扩展防止了进一步的虚假扩展,并减少了云管理系统中需要支持的自动扩展系统的数量。此外,网络资源通常不能自动伸缩。在本文中,我们描述了一个云资源自动扩展系统,解决并克服了上述限制。
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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