Incremental consistency checking for pervasive context

Abstract:Applications in pervasive computing are typically required to interact seamlessly with their changing environments. To provide users with smart computational services, these applications must be aware of incessant context changes in their environments and adjust their behaviors accordingly. As these environments are highly dynamic and noisy, context changes thus acquired could be obsolete, corrupted or inaccurate. This gives rise to the problem of context inconsistency, which must be timely detected in order to prevent applications from behaving anomalously. In this paper, we propose a formal model of incremental consistency checking for pervasive contexts. Based on this model, we further propose an efficient checking algorithm to detect inconsistent contexts. The performance of the algorithm and its advantages over conventional checking techniques are evaluated experimentally using Cabot middleware.
Grants:HKUST 6167/04E
Links:PDF
Citation:Chang Xu, S.C. Cheung, and W. K. Chan, "Incremental consistency checking for pervasive context," in Proceedings of the 28th International Conference on Software Engineering (ICSE 2006), pages 292-301, ACM Press, New York (2006).
Remarks:[Acceptance rate: 9.1%, 36 out of 395]
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