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Towards understanding the runtime configuration management of do-it-yourself content delivery network applications over public clouds

机译:旨在了解公共云上自行完成内容交付网络应用程序的运行时配置管理

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Cloud computing is a new paradigm shift which enables applications and related content (audio, video, text, images, etc.) to be provisioned in an on-demand manner and being accessible to anyone anywhere in the world without the need for owning expensive computing and storage infrastructures. Interactive multimedia content-driven applications in the domains of healthcare, aged-care, and education have emerged as one of the new classes of big data applications. This new generation of applications need to support complex content operations including production, deployment, consumption, personalization, and distribution. However, to efficiently provision these applications on the Cloud data centres, there is a need to understand their runtime resource configurations. For example: (ⅰ) where to store and distribute the content to and from driven by end-user Service Level Agreements (SLAs)? (ⅱ) How many content distribution servers to provision? And (ⅲ) what Cloud VM configuration (number of instances, types, speed, etc.) to provision? In this paper, we present concepts and factors related to engineering such content-driven applications over public Clouds. Based on these concepts and factors, we propose a performance evaluation methodology for quantifying and understanding the runtime configuration of these classes of applications. Finally, we conduct several benchmark driven experiments for validating the feasibility of the proposed methodology.
机译:云计算是一种新的范式转变,它使应用程序和相关内容(音频,视频,文本,图像等)可以按需提供,并且世界上任何地方都可以访问,而无需拥有昂贵的计算资源和存储基础架构。在医疗保健,老年护理和教育领域中,交互式多媒体内容驱动的应用程序已成为大数据应用程序的新类别之一。新一代应用程序需要支持复杂的内容操作,包括生产,部署,使用,个性化和分发。但是,为了在Cloud数据中心上有效地配置这些应用程序,需要了解其运行时资源配置。例如:(ⅰ)在最终用户服务级别协议(SLA)的驱动下,内容在哪里存储和分发? (ⅱ)要配置多少个内容分发服务器?以及(ⅲ)要配置什么Cloud VM配置(实例数,类型,速度等)?在本文中,我们介绍了与在公共云上设计此类内容驱动的应用程序有关的概念和因素。基于这些概念和因素,我们提出了一种性能评估方法,用于量化和理解这些应用程序类别的运行时配置。最后,我们进行了一些基准测试实验,以验证所提出方法的可行性。

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