Understanding and Using Context
Personal and Ubiquitous Computing
Towards a Theory of Context Spaces
PERCOMW '04 Proceedings of the Second IEEE Annual Conference on Pervasive Computing and Communications Workshops
Revising Markov Boundary for Multiagent Probabilistic Inference
IAT '04 Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology
ACAI: agent-based context-aware infrastructure for spontaneous applications
Journal of Network and Computer Applications
Merging Context Perspectives: An Approach to Adaptive Agent Reasoning in Pervasive Computing Systems
PERCOMW '06 Proceedings of the 4th annual IEEE international conference on Pervasive Computing and Communications Workshops
Dynamic multiagent probabilistic inference
International Journal of Approximate Reasoning
ISDA '08 Proceedings of the 2008 Eighth International Conference on Intelligent Systems Design and Applications - Volume 01
An Agent-Based Context-Aware Middleware for Pervasive Computing
ISISE '08 Proceedings of the 2008 International Symposium on Information Science and Engieering - Volume 02
Ubiquitous Computing-Oriented Distributed Fuzzy Reasoning Petri Net Modeling and Simulation
PDCAT '09 Proceedings of the 2009 International Conference on Parallel and Distributed Computing, Applications and Technologies
A multi-agent systems approach to distributed bayesian information fusion
Information Fusion
A survey of context modelling and reasoning techniques
Pervasive and Mobile Computing
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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Context awareness service is one of the key features in ubiquitous computing system. In heterogeneous pervasive computing system, effective context modeling and reasoning are important to enable the collaboration and distributed reasoning among the agents. The effectiveness of the previous approaches for distributed reasoning significantly degrades when a large number of agents are involved. In order to solve this problem we propose a layered context model facilitating distributed reasoning. We also propose an approach for grouping the agents based on their importance. The proposed approaches can reduce the amount of resource required for updating the context information, and allow the system to more stably and flexibly adapt to the changing environment. The performance of the proposed scheme is verified by computer simulation, and it shows that the trust of reasoning outcome is greatly enhanced with less resource than the earlier scheme.