Similarity based optimization context awareness in remote healthy service

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 similarity based context reasoning to optimize system performance. The performance of the proposed scheme is verified in remote health service, and it shows that the trust of reasoning outcome is greatly enhanced and the data traffic is effectively reduced.