Caching Context Information in Pervasive Systems

Anandarajah, Myilone (2007). Caching Context Information in Pervasive Systems MPhil Thesis, School of Information Technology and Electrical Engineering, University of Queensland.

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Author Anandarajah, Myilone
Thesis Title Caching Context Information in Pervasive Systems
School, Centre or Institute School of Information Technology and Electrical Engineering
Institution University of Queensland
Publication date 2007
Thesis type MPhil Thesis
Supervisor Associate professor Jadwiga Indulska
Subjects 08 Information and Computing Sciences
Abstract/Summary Context information can be defined as information about the situation of a person, place or object. Context-aware systems use context information to adapt their behaviour or the content they provide. The role of context management systems is to store, retrieve and evaluate context information on behalf of context-aware applications. Context management systems store context information in repositories, which can be distributed. This research addressed the problem of disconnections in context-aware systems. Disconnections in a context-aware system may occur because of node mobility, network failures or node failures. A research opportunity lay in improving the robustness of context-aware systems to disconnections. While traditional distributed systems methods of improving robustness in the face of disconnections can be applied to context-aware systems, the additional metadata available to context-aware systems may be leveraged to provide smarter caching algorithms. This research tested the above hypothesis by pursuing research into “smart” caching algorithms for context information. Many modern approaches to building context-aware systems use context models to capture relevant concepts and relationships between these concepts. These models are expressed using a modelling language. For the purposes of this research , we focus on the Context Modelling Language (CML), as it provides specific support for context-aware systems. CML supports sophisticated fact-based context modelling in which facts may be associated with a range of attributes, including its quality, classification as static, profiled, sensed or derived and temporal constraints. This thesis shows how these metadata can be used in conjunction with the inherent relational nature of CML to develop efficient caching algorithms for context information.

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Created: Fri, 21 Nov 2008, 16:14:00 EST