Heuristics-based strategies for resolving context inconsistencies in pervasive computing applications

Abstract:Context-awareness allows pervasive applications to adapt to changeable computing environments. Contexts, the pieces of information that capture the characteristics of environments, are often error-prone and inconsistent due to noises. Various strategies have been proposed to enable automatic context inconsistency resolution. They are formulated on different assumptions that may not hold in practice. This causes applications to be less context-aware to different extents. In this paper, we investigate such impacts and propose our new resolution strategy. We conducted experiments to compare our work with major existing strategies. The results showed that our strategy is both effective in resolving context inconsistencies and promising in its support of applications using contexts.
Grants:GRF 612306, GRF 111107, HKBU 1/05C, NSFC 60736015, NBRC 2006CB303000
Links:PDF, DOI
Citation:Chang Xu, S.C. Cheung, W.K. Chan, and Chunyang Ye, "Heuristics-based strategies for resolving context inconsistencies in pervasive computing applications", in Proceedings of the 28th International Conference on Distributed Computing Systems (ICDCS 2008), (Beijing, China, June 17-20, 2008,)  pages 709-717, IEEE Computer Society Press, Los Alamitos, California (2008).
Remarks:[Acceptance rate: 16.0%, 102 out of 638]
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