一种面向上下文感知计算的建模方法

Research on Modeling Approach Towards Context-aware Computing

上下文感知计算是指系统能发现并有效利用上下文信息(如用户位置,时间,环境参数,邻近的设备和人员,用户活动等)进行计算的一种计算模式。通常来说,上下文感知计算系统都是复杂的大规模分布式混合系统,如何对其有效建模是研究中的一个重要问题。本文提出一种基于PtolemyⅡ的上下文感知计算建模方法。通过将FSM与层次化建模相结合减少FSM的状态数目,然后扩展FSM中状态,使其能执行预先定义的脚本或被再次建模。该建模方法能有效地支持上下文感知计算系统建模及快速原型构建。

Context- aware computing is a mobile computing paradigm in which applications can discover and take advantage of contextual information. In general, context - aware is a distributed, large scale, sophisticated and hybrid system. In this paper, we present a Ptolemy Ⅱ based modeling approach, in this approach, we combine a hierarchical modeling methodology with finite state machine （FSM）, and limit the state number of the FSM, then extend state to have ability to execute predefined scripts and modeled by other components. This approach is very useful and has many benefits in context - aware computing development. It can be used to reduce complexity of context - aware system modeling and support rapid prototype development.