A Context Inference Framework based on Fuzzy Colored Timed Petri Nets

In context-aware computing environment, some context is characterized by a single event, but many other contexts are determined by a sequence of events which occur with some timing constraints. Therefore, context inference should be conducted by monitoring the sequence of event occurrence along with checking their conformance with timing constraints. Some context could be described with fuzzy which can be easily used in situation description. Multiple entities may interact with a service system, and thus the context inference mechanism should be facilitated to handle multiple entities in the same situation. This paper proposes a context inference model which is based on Petri net. The model represents and handles the sequential occurrence of some events along with involved timing constraints, deals with the multiple entities using the colored tokens, and employs the concept of fuzzy tokens to support the fuzzy concepts. This work was supported by the Korea Research Foundation Grant funded by the Korean Government(MOEHRD) (The Regional Research Universities Program/Chungbuk BIT Research-Oriented University Consortium)