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A Middleware-Centric Optimization Approach for the Automated Provisioning of Services in the Cloud

机译:在云中自动提供服务的以中间件为中心的优化方法

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The on-demand provisioning of services, a cloud-based extension for traditional service-oriented architectures, improves the handling of services in usage scenarios where they are only used rarely and irregularly. However, the standard process of service provisioning and de-provisioning shows still some shortcomings when applying it in real world. In this paper, we introduce a middleware-centric optimization approach that can be integrated in the existing on-demand provisioning middleware in a loosely coupled manner, changing the standard provisioning and de-provisioning behavior in order to improve it with respect to cost and time. We define and implement a set of optimization strategies, evaluate them based on a real world use case from the eScience domain and provide qualitative as well as quantitative decision support for effectively selecting and parametrizing a suitable strategy. Altogether, our work improves the applicability of the existing on-demand provisioning approach and system in real world, including guidance for selecting the suitable optimization strategy for specific use cases.
机译:按需提供服务是对传统的面向服务的体系结构的基于云的扩展,它改善了在很少或不定期使用的使用情况下对服务的处理。但是,在实际应用中,服务提供和取消提供的标准过程仍然显示出一些缺点。在本文中,我们介绍了一种以中间件为中心的优化方法,该方法可以以松散耦合的方式集成到现有的按需供应中间件中,更改标准的供应和取消供应行为,以便在成本和时间方面进行改进。 。我们定义并实施了一组优化策略,根据eScience领域的实际使用案例对它们进行评估,并提供定性和定量决策支持,以有效地选择和参数化合适的策略。总之,我们的工作改善了现有按需供应方法和系统在现实世界中的适用性,包括为特定用例选择合适的优化策略的指南。

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