A Modular SystemC RTOS Model for Uncertainty Analysis

Nowadays the complexity of embedded systems is constantly increasing and several different types of applications concurrently execute on the same computational platform. Hence these systems have to satisfy real-time constraints and support real-time communication. The design and verification of these systems is very complex, full formal verification is not always possible and the run-time verification is the only feasible path to follow. In this context, the possibility to simulate their behavior becomes a crucial aspect. This paper proposes a SystemC modular RTOS model to assist the design and the verification of real-time embedded systems. The model architecture has been designed to capture all the typical functionalities that every RTOS owns, in order to easily reproduce the behavior of a large class of RTOS. The RTOS model can support functional simulation for design space exploration to rapidly evaluate the impact of different RTOS configurations (such as scheduling policies) on the overall system performances. Moreover the model can be used for software verification by implementing specific RTOS APIs over the generic services provided by the model, allowing the simulation of a real application without changing any instruction. The proposed approach enables the user to model non-deterministic behaviors at architectural and application level by means of probabilistic distributions. This allows to assess system performances of complex embedded systems under uncertain behavior (e.g. execution time). A use case is proposed considering an instance of the model compliant with the ARINC 653 specification, which requires spatial and temporal segregation, and where typical RTOS performances are assessed given the probability distributions of execution time and aperiodic task activation.