A Generic Context Interpreter for Pervasive Context-Aware Systems

A Generic Context Interpreter for Pervasive Context-Aware Systems

Been-Chian Chien (National University of Tainan, Taiwan) and Shiang-Yi He (National University of Tainan, Taiwan)
DOI: 10.4018/978-1-4666-2785-7.ch017


Developing pervasive context-aware systems to construct smart space applications has attracted much attention from researchers in recent decades. Although many different kinds of context-aware computing paradigms were built of late years, it is still a challenge for researchers to extend an existing system to different application domains and interoperate with other service systems due to heterogeneity among systems This paper proposes a generic context interpreter to overcome the dependency between context and hardware devices. The proposed generic context interpreter contains two modules: the context interpreter generator and the generic interpreter. The context interpreter generator imports sensor data from sensor devices as an XML schema and produces interpretation scripts instead of interpretation widgets. The generic interpreter generates the semantic context for context-aware applications. A context editor is also designed by employing schema matching algorithms for supporting context mapping between devices and context model.
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The term context-aware first appeared in 1994 mentioned by Schilit and Theimer (1994). Since then, various context-aware computing architectures were proposed: The Context Toolkit (Dey & Abowd, 1999; Dey, Abowd, & Salber, 2001) provided context interpretation using widgets and a set of object-oriented APIs to offer the creation of service components. The Hydrogen (Hofer et al., 2002) is a framework based on layered architecture in which contains the adaptor layer, the management layer and the application layer. The Gaia project (Roman et al., 2002) is a middle-ware based architecture; the system consists of Gaia kernel and application framework to support the development and execution of mobile applications. Another middle-ware system, SOCAM (Gu, Pung, & Zhang, 2004) uses a central server called context interpreter to obtain context data for building and prototyping of context-aware services. The CORTEX system (Biegel & Cahill, 2004) is also a middle-ware structure based on sentient object model which supports context-aware services in an ad-hoc mobile environment.

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