Context reasoning using extended evidence theory in pervasive computing environments

Authors:
Daqiang Zhang;Minyi Guo;Jingyu Zhou;Dazhou Kang;Jiannong Cao
Affiliations:
Department of Computer Science, Shanghai Jiao Tong University, Shanghai, 200240, PR China;Department of Computer Science, Shanghai Jiao Tong University, Shanghai, 200240, PR China;Department of Computer Science, Shanghai Jiao Tong University, Shanghai, 200240, PR China;Department of Computer Science, Nanjing University, Nanjing, 210089, PR China;Department of Computing, The Hong Kong Polytechnic University, Hong Kong
Venue:
Future Generation Computer Systems
Year:
2010

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Abstract

Most existing context reasoning approaches implicitly assume that contexts are precise and complete. This assumption cannot be held in pervasive computing environments, where contexts are often imprecise and incomplete due to unreliable connectivity, user mobility and resource constraints. To this end, we propose an approach called CRET: Context Reasoning using extended Evidence Theory. CRET applies the evidence theory to context reasoning in pervasive computing environments. Because evidence theory is limited by two fundamental problems-computation-intensiveness and Zadeh paradox, CRET presents evidence selection and conflict resolution strategies. Empirical study shows that CRET is desirable for pervasive applications.