A state-based approach to context modeling and computing
Songhui Yue, Randy Smith, Songqing Yue · 2017
Context-aware computing is one of the most essential computing paradigms in pervasive computing and Internet of Things (IoT) areas. However, current context-aware computing is still in lack of good representation models, particularly in modeling proactive behaviors and historical context data. State diagrams have proven to be an effective modeling method for modeling system behaviors. For context-aware computing, explicitly putting forward states of high-level context can be beneficial and intrigue new angles of understanding and modeling activities. In this paper, we firstly propose a state-based context model, and based on the model, we introduce Context Mealy State Machines (CMSM) for simulating state changes of context attribute, situation, and context, which imply important behaviors of context. Examples are given to illustrate how to build simple CMSMs and how to use our approach for supporting context prediction.