Ensuring IoT Controller Reliability with Colored Generalized Stochastic Petri Net

In IoT systems managing multiple devices simultaneously, errors in system controllers often undermine intended operations. Formal verification offers a method to assess system reliability. Colored Generalized Stochastic Petri Net (CGSPN), a formal language, facilitate correctness checks of such systems. This study proposes a verification approach by translating a C++-based system controller of a self-service machine into a CGSPN models and validating it using the Snoopy Tool. Mapping techniques employed to transform components in the controller into CGSPN models are provided. Results demonstrate the method’s efficacy in verifying system safety properties, simulating system events, and enabling quantitative verification.