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Categorization and modelling of quality in context information

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dc.contributor.author Razzaque, Mohammed Abhur
dc.contributor.author Dobson, Simon
dc.contributor.author Nixon, Paddy
dc.date.accessioned 2012-07-13T13:20:34Z
dc.date.available 2012-07-13T13:20:34Z
dc.date.issued 2006
dc.identifier.uri http://hdl.handle.net/10344/2355
dc.description peer-reviewed en_US
dc.description.abstract Pervasive computing environments are dynamic and heterogeneous. They are required to be self-managing and autonomic, demanding minimal user’s guidance. In pervasive computing, contextaware adaptation is a key concept to meet the varying requirements of different clients. In order to enable context-aware adaptation, context information must be gathered and eventually presented to the application performing the adaptation. It is clear that some form of context categorization will be required given the wide range of heterogeneous context information. Categorizations can be made from different viewpoints such as conceptual viewpoint, measurement viewpoint, temporal characteristics viewpoint and so on. To facilitate the programming of context-aware applications, modelling of contextual information is highly necessary. Most of the existing models fail both to represent dependency relations between the diverse context information, and to utilize these dependency relations. A number of them support narrow classes of context and applied to limited types of application, and most do not consider the issue of Quality of Contextual Information (QoCI). Along with a detailed context categorization, this paper will analyse existing context models and discuss their handling of dependency issues. It uses this analysis to derive a methodology for quality context information modelling in context aware computing. en_US
dc.language.iso eng en_US
dc.publisher American Scientific Publishers en_US
dc.relation.ispartofseries Journal of Trusted and Autonomic Computing;
dc.subject autonomic computing en_US
dc.subject programming en_US
dc.title Categorization and modelling of quality in context information en_US
dc.type info:eu-repo/semantics/workingPaper en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.contributor.sponsor SFI en_US
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US

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