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

机译:一种以中间件为中心的优化方法,用于云中的自动配置服务

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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:服务的按需配置,一种用于传统服务型体系结构的基于云的扩展,可提高使用情况的服务中的服务,其中它们只能很少使用。但是,在现实世界中将其应用时,服务供应和解雇的标准过程显示出一些缺点。在本文中,我们介绍了一种以中间物品为中心的优化方法,可以以松散耦合的方式集成在现有的按需供应中间件中,改变标准供应和解放行为,以便在成本和时间方面改善其。我们定义并实施一组优化策略,根据来自埃斯特级域的真实世界用例评估它们,并提供定性的以及定量决策支持,以有效地选择和参加合适的策略。完全,我们的工作提高了现有的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导。

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