Cyber-physical systems are systems that couple both elements from numerical computing and physical elements. Systems containing a control loop in order to drive a vehicle in a real environment can be considered as a cyber-physical system. Aircrafts fit into this category. The uses of simulation in conception and validation phases are more and more important, due to increasing complexity of embedded systems in aircrafts. In order to receive the full benefit of a test realised in simulated environment, one must prove that the simulated system is valid. Certain tests obliged simulated aircrafts to impose a reproducibility guarantee. These guarantees do not exist in real aircrafts, which have non reproducible behaviors. Cyber-physical systems simulation require the assembly of two types of models: - Discretized models: Mathematical approximation of continuous phenomena. - Discrete models. In a complex system such as an aircraft, the execution of the simulation uses a distributed simulation environment. Communications and synchronizations are required in the assembly of models, which are allocated to processors. It should be noted that the control loops complicate the sequence of simulator executions. Besides the fidelity of every models, the assembly (temporal organization and interaction) must reflects reality in order to achieve simulation validity. This assembly is called the simulation scheduling. In our context, this scheduling is a distributed scheduling. Currently, schedulings are obtained empirically. This method does not allow estimating the validity of a scheduling a priori. In order to increase the usage of simulation, we should guarantee the validity of their schedulings more easily. The main objective consists in defining a formal method to determine a priori the validity of a simulation scheduling, for a distributed simulation of a cyber-physical system. The goal is to prove by analytical methods that an assembly of models should be sufficiently representative depending of the objectives of a given test on a given platform.