泛在应用的上下文质量模型

Siliang Tang, Jianhua Yang, Zhaohui Wu
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引用次数: 22

摘要

上下文质量(Quality of Context, QoC)在上下文推理、上下文精炼、安全策略配置等方面至关重要。目前已有许多研究通过量化质量质量参数来模拟环境及其质量。然而,这些质量模型强调的是信息固有的质量要求,而没有充分考虑上下文感知应用和环境状况对质量要求的影响。本文提出了一种基于OWL-DL的上下文质量模型,该模型与情境相关,可由上下文感知应用指定。此外,由于QoC模型与上下文处理相关,因此引入了上下文处理基础结构。此外,还实现了一个上下文信息服务原型,以支持与应用程序和情况相关的QoC纠正。最后,我们通过一个储藏室场景和上下文文件系统应用的案例研究,在先锋III -AT移动机器人和基于fuse的上下文文件系统的帮助下,证明了这种方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Context Quality Model for Ubiquitous Applications
Quality of Context (QoC) is critical in context reasoning, context refining, security policy configuring, etc. Many researches have been presented to model context and its quality by quantifying QoC-parameters. However, these quality models emphasis on the information-inherent QoC, while the influence of context-aware applications and environment situation on QoC is not well considered. In this paper, we will propose a novel context quality model based on OWL-DL, which is related with situation and can be specified by context-aware applications. Moreover, a context processing infrastructure is introduced, since QoC model is relevant to context processing. Furthermore, a context information service prototype is implemented to support application and situation related QoC rectification. Finally, we demonstrate the efficacy of this approach through a storeroom scenario and a case study of context file system application with the help of a Pioneer III -AT mobile robot and a FUSE-based Context file system.
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