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EXCLAIM framework: a monitoring and analysis framework to support self-governance in Cloud Application Platforms

机译:EXCLAIM框架:一个监视和分析框架,以支持云应用程序平台中的自治

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摘要

The Platform-as-a-Service segment of Cloud Computing has been steadily growing over the past several years, with more and more software developers opting for cloud platforms as convenient ecosystems for developing, deploying, testing and maintaining their software. Such cloud platforms also play an important role in delivering an easily-accessible Internet of Services. They provide rich support for software development, and, following the principles of Service-Oriented Computing, offer their subscribers a wide selection of pre-existing, reliable and reusable basic services, available through a common platform marketplace and ready to be seamlessly integrated into users' applications. Such cloud ecosystems are becoming increasingly dynamic and complex, and one of the major challenges faced by cloud providers is to develop appropriate scalable and extensible mechanisms for governance and control based on run-time monitoring and analysis of (extreme amounts of) raw heterogeneous data.ududIn this thesis we address this important research question -- extbf{how can we support self-governance in cloud platforms delivering the Internet of Services in the presence of large amounts of heterogeneous and rapidly changing data?} To address this research question and demonstrate our approach, we have created the Extensible Cloud Monitoring and Analysis (EXCLAIM) framework for service-based cloud platforms. The main idea underpinning our approach is to encode monitored heterogeneous data using Semantic Web languages, which then enables us to integrate these semantically enriched observation streams with static ontological knowledge and to apply intelligent reasoning. This has allowed us to create an extensible, modular, and declaratively defined architecture for performing run-time data monitoring and analysis with a view to detecting critical situations within cloud platforms. ududBy addressing the main research question, our approach contributes to the domain of Cloud Computing, and in particular to the area of autonomic and self-managing capabilities of service-based cloud platforms. Our main contributions include the approach itself, which allows monitoring and analysing heterogeneous data in an extensible and scalable manner, the prototype of the EXCLAIM framework, and the Cloud Sensor Ontology. Our research also contributes to the state of the art in Software Engineering by demonstrating how existing techniques from several fields (i.e., Autonomic Computing, Service-Oriented Computing, Stream Processing, Semantic Sensor Web, and Big Data) can be combined in a novel way to create an extensible, scalable, modular, and declaratively defined monitoring and analysis solution.
机译:过去几年中,云计算的平台即服务部分一直在稳步增长,越来越多的软件开发人员选择云平台作为开发,部署,测试和维护软件的便捷生态系统。此类云平台在提供易于访问的服务互联网方面也起着重要作用。他们为软件开发提供了丰富的支持,并且遵循面向服务的计算原理,为订户提供了广泛的选择,它们可以通过通用平台市场获得,并且可以无缝地集成到用户中,这些服务已经存在,可靠且可重用。的应用程序。这样的云生态系统变得越来越动态和复杂,云提供商所面临的主要挑战之一是基于运行时监视和分析(大量)原始异构数据来开发适当的可扩展和可扩展的治理和控制机制。 ud ud在本文中,我们解决了这个重要的研究问题- textbf {我们如何在存在大量异构且快速变化的数据的情况下,在提供服务互联网的云平台中如何支持自治?}质疑并证明我们的方法,我们已经为基于服务的云平台创建了可扩展云监控和分析(EXCLAIM)框架。支持该方法的主要思想是使用语义Web语言对监视的异构数据进行编码,然后使我们能够将这些语义丰富的观察流与静态本体论知识集成在一起,并应用智能推理。这使我们能够创建可扩展的,模块化的,定义性定义的架构,以执行运行时数据监视和分析,以检测云平台内的紧急情况。 ud ud通过解决主要研究问题,我们的方法有助于云计算领域,尤其是基于服务的云平台的自主性和自我管理能力领域。我们的主要贡献包括该方法本身,该方法允许以可扩展和可扩展的方式监视和分析异构数据,EXCLAIM框架的原型以及Cloud Sensor Ontology。我们的研究还展示了如何以新颖的方式组合来自多个领域(例如,自主计算,面向服务的计算,流处理,语义传感器网络和大数据)的现有技术,从而为软件工程领域的最新发展做出了贡献创建可扩展,可扩展,模块化和声明式定义的监视和分析解决方案。

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    Dautov Rustem;

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  • 年度 2015
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