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A middleware based layered framework for the quality management of context-aware pervasive applications

机译:基于中间件的分层框架,用于上下文普及应用程序的质量管理

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With the rapid development of pervasive computing, more and more sensors based applications have been implemented. And many problems occur in the process of providing stable basis for the normal working of these systems. One of them is how to continuously monitor/capture and interpret the environment related information efficiently to assure high context awareness. Many attentions have been paid to the research of the context-aware pervasive applications. However, most of them just use the raw context directly or take the Quality of Context (QoC) into account in just one or two steps. Therefore, we propose a layered middleware based context-aware framework that support QoC management through various layers. By this framework we can refinery raw context, discard duplicate and inconsistent context so as to protect and provide QoS-enriched context information of users to context-aware applications and services.
机译:随着普遍计算的快速发展,已经实施了越来越多的基于传感器的应用程序。 在为这些系统的正常工作提供稳定基础的过程中发生了许多问题。 其中一个是如何有效地连续监控/捕获和解释环境相关信息,以确保高背景意识。 许多关注已经支付了对环境感知普遍应用的研究。 但是,其中大多数只需直接使用原始上下文或以一两步即时考虑上下文(QoC)。 因此,我们提出了一种基于层的中间件的上下文感知框架,通过各种图层支持QoC管理。 通过此框架,我们可以炼油效果原始上下文,丢弃重复和不一致的上下文,以便保护和提供QoS的上下文信息,以使用户的上下文感知应用程序和服务。

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