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An Adaptation Reasoning Approach for Large Scale Component-based Applications

机译:大规模基于组件的应用的自适应推理方法

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There is a growing demand for context-aware applications that can dynamically adapt to their run-time environment. An application offers a collection of functionalities that can be realized through a composition of software components and/or services that are made available at runtime. With the availability of alternative variants of such components and/or services that provide the basic functionalities, while differ in extra-functional characteristics, characterized by quality of services (QoS), an unforeseen number of application variants can be created. The variant that best fits the current context is selected through adaptation reasoning, which can suffer from the processing capabilities of resource-scarce mobile devices, especially when a huge number of application variants needs to be reason about. In this paper, we present a reasoning approach, which provides a meaningful adaptation decision for adaptive applications having a large number of variants within a reasonable time frame. The approach is validated through two arbitrary applications with large number of variants.Keywords: self-adaptation, ubiquitous computing, adaptation reasoning, variability, scalability, utility function
机译:可以动态适应其运行时环境的上下文感知应用程序的需求不断增长。应用程序提供了功能的集合,这些功能可以通过在运行时提供的软件组件和/或服务的组合来实现。由于提供了基本功能的此类组件和/或服务的替代变体的可用性,而在以服务质量(QoS)为特征的额外功能特征方面却有所不同,因此会创建数量无法预料的应用变体。通过适应性推理选择最适合当前上下文的变体,这可能会受到资源稀缺的移动设备的处理能力的影响,特别是在需要考虑大量应用程序变体的情况下。在本文中,我们提出了一种推理方法,该方法为合理时间范围内具有大量变体的自适应应用程序提供了有意义的自适应决策。该方法已通过两个具有大量变体的任意应用程序进行了验证。关键字:自适应,普适计算,适应推理,可变性,可伸缩性,效用函数

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