RailRED: a Node-RED-based framework for modeling Train Control Management Systems

The modeling and simulation of Internet of Things (IoT) and Industrial IoT (IIoT) systems allow practitioners to obtain valuable insights into the system's behavior before their actual deployment in the field. Early designing permits the analysis of the interactions among the involved entities, evaluating the effects of modifications, and understanding the impact of failures on the system. In particular, this is exacerbated in the context of IoT/IIoT, which is characterized by multiple and heterogeneous subsystems, different processing levels, and communication protocols. In such a direction, recent innovations in IT devices have enabled the rail industry to gather information from Train Control and Monitoring Systems (TCMS) to check conditions constantly and prevent issues, thus improving reliability and safety and, in some cases, leading to cost-saving by optimizing maintenance resources. In such a scenario, this paper presents RailRED, a framework for simulating and prototyping a TCMS based on the Node-RED tool. In RailRED, the main TCMS subsystems are modeled using Node-RED flows, while the subsystem interconnections are performed through a low footprint and encrypted gateway based on the MQTT protocol. The proposal can also generate diagnostic data that mimic the behavior of a real-world TCMS. RailRED communication latency and its ability to generate diagnostic data have been analyzed, with the latter evaluated by using clusters of diagnostic events collected from a real-world TCMS running on a high-speed train.