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On Impact-Oriented Automatic Resolution of Pervasive Context Inconsistency

By Chang Xu, S. C. Cheung, W. K. Chan and Chunyang Ye


Context-awareness is a capability that allows applications in pervasive computing to adapt themselves continuously to changing contexts of their environments. However, contexts from physical environments may be inconsistent. It affects the correctness of these applications. Existing resolution strategies for context inconsistency have diverse adverse impacts on the contextawareness of applications, such as feeding different amounts of contexts to the applications. In this paper, we examine the impacts of inconsistency resolution and study the extent to which their effects on context-awareness can be reduced. We conduct simulation experiments of two pervasive computing applications. The experimental results show that existing inconsistency resolution strategies adversely affect the context-awareness of applications. This motivates the importance of deploying an impact-oriented approach to respect context-awareness in inconsistency resolution

Topics: Categories and Subject Descriptors D.2.4 [Software Engineering, Software/Program Verification – Validation. General Terms Measurement, Performance, Verification Keywords Inconsistency Resolution, Pervasive Computing
Year: 2007
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