2022/11/03 by Kevin Zagalo, Zagalo, Kevin, Avner Bar‐Hen +3
Computer Science · #FOS: Electrical engineering #FOS: Mathematics #Formal Methods in Verification #Real-Time Systems Scheduling #Software Reliability and Analysis Research #Statistics Theory (math.ST) #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2211.01720
openalex publication_date 2022/11/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Real-time systems consist of a set of tasks, a scheduling policy, and a system architecture, all constrained by timing requirements. Many everyday embedded systems, within devices such as airplanes, cars, trains, and spatial probes, operate as real-time systems. To ensure safe failure rates, response times-the time required for the exection of a task-must be bounded. Rate Monotonic real-time systems prioritize tasks according to their arrival rate. This paper focuses on the use of the central limit of response times built in \citezagalo2022 and an approximation of their distribution with an inverse Gaussian mixture distribution. The distribution parameters and their associated failure rates are estimated through a suitable re-parameterization of the inverse Gaussian distribution and an adapted Expectation-Maximization algorithm. Extensive simulations demonstrate that the method is well-suited for the approximation of failure rates. We discuss the extension of such method to a chi-squared independence test adapted to real-time systems.