Modeling the contexts without distracting the perspectives of the agents in distributed reasoning

Context-awareness service is one of the key features of ubiquitous paradigm. To intelligently and sensitively deal with the dynamic environment, a methodology effectively enabling the agent-based distributed reasoning needs to be developed. The existing modeling approaches focus on scenario-based acquisition, management, and representation of context. However, they are difficult to be adapted to agent-based distributed reasoning. In this paper we propose a modeling approach for distributed reasoning which permits merging of different perspectives of context models without the distraction of individual aspects. Moreover, a context-awareness engine is developed to support agent-based context-awareness service. The effectiveness of the proposed methodology is verified by computer simulation which reveals that the proposed approach allows much more accurate and stable reasoning than the earlier scheme.