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Inconsistency Detection and Resolution for Context-Aware Middleware Support

By Chang Xu and S. C. Cheung

Abstract

Context-awareness is a key feature of pervasive computing whose environments keep evolving. The support of context-awareness requires comprehensive management including detection and resolution of context inconsistency, which occurs naturally in pervasive computing. In this paper we present a framework for realizing dynamic context consistency management. The framework supports inconsistency detection based on a semantic matching and inconsistency triggering model, and inconsistency resolution with proactive actions to context sources. We further present an implementation based on the Cabot middleware. The feasibility of the framework and its performance are evaluated through a case study and a simulated experiment, respectively

Topics: Categories and Subject Descriptors D.2.1 [Software Engineering, Requirements/Specifications – Methodologies General Terms Algorithms, Design, Management, Performance Keywords Pervasive Computing, Context Modeling, Context Consistency Management, Semantic Matching, Proactive Repairing
Year: 2005
OAI identifier: oai:CiteSeerX.psu:10.1.1.352.2014
Provided by: CiteSeerX
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