Binary Context Tree Based Middleware for Next Generation Context Aware Networks

T. Bilen, B. Canberk
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引用次数: 4

Abstract

Context aware mobile applications are special types of context aware network systems that process gathered data from environment with context cycle functionalities and special infrastructure to obtain context information. Here, modelling and reasoning are most important functionalities and middleware is one of the common infrastructure to implement these functionalities. Essentially, techniques that are used in these modelling and reasoning processes should have flexible, well-structured, fast features as well as robust quality checking mechanisms. With these motivations, in this paper, we propose our context aware mobile application management system infrastructure with an exemplary smart workplace scenario implementation. In this system, we use our new middleware to implement context cycle functionalities such as acquisition, modelling, reasoning, distribution and extra features. Also, we propose priority based binary context tree approach to enable extendable, fast and well-structured modelling technique. To enable priority feature of tree, priority expression and stack data structure are used and all context attributes represented with binary values on the tree. Besides all these, to support our modelling technique, we provide new formal language with alphabets, grammar rules and words for formal based logic rule reasoning approach. Moreover these features, our proposed middleware enable context history keeping functionality. Using these informations with simple implementations, we show our modelling approach has %12 better time performance and our system has %50 higher performance value in terms of connected devices.
基于二叉上下文树的下一代上下文感知网络中间件
上下文感知移动应用程序是一种特殊类型的上下文感知网络系统,它处理从具有上下文循环功能和特殊基础设施的环境中收集的数据,以获取上下文信息。在这里,建模和推理是最重要的功能,中间件是实现这些功能的常用基础设施之一。从本质上讲,在这些建模和推理过程中使用的技术应该具有灵活的、结构良好的、快速的特征以及健壮的质量检查机制。基于这些动机,在本文中,我们提出了具有示例性的智能工作场所场景实现的上下文感知移动应用程序管理系统基础设施。在这个系统中,我们使用新的中间件来实现上下文循环功能,如获取、建模、推理、分发和额外的功能。此外,我们提出了基于优先级的二叉上下文树方法,以实现可扩展、快速和结构良好的建模技术。为了实现树的优先级特性,使用了优先级表达式和堆栈数据结构,所有上下文属性都在树上用二进制值表示。除此之外,为了支持我们的建模技术,我们为基于形式的逻辑规则推理方法提供了新的具有字母、语法规则和单词的形式语言。此外,我们建议的中间件还支持保持上下文历史记录的功能。使用这些信息和简单的实现,我们表明我们的建模方法具有更好的时间性能,并且我们的系统在连接设备方面具有更高的性能值% 50%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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