Enhancing Real-Time Performance: a Multithreaded Method for Fuzzy Timed Petri Net Modelling
Abdelilah Serji, El Bekkaye Mermri, Mohammed Blej · 2025
Fuzzy Time Petri Nets (FTPNs) have been determined to be effective in modelling complex real-time systems characterized by uncertainty and imprecise data. However, many program techniques encounter performance limitations, especially in large-scale contexts with numerous state transitions. This paper introduces a method that applies multithreading programming to improve the efficiency of state transition rules in FTPN models. The proposed method significantly decreases processing times while enhancing overall system responsiveness by dividing the FTPN structure according to modelling rules and running transitions in parallel when tasks are executed simultaneously. We present our method with a step-by-step implementation outline and a performance evaluation through case studies. To validate our process, we implemented it in a real-time system, and the results show that integrating multithreaded programming into FTPN can improve computing speed by as much as 35 % compared to conventional single-threaded methods. Real-time automated decision-making and anomaly detection applications benefit significantly from this advance, which provides a practical and scalable framework for dealing with complex system dynamics.