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Main Authors: Zagalo, Kevin, Bar-Hen, Avner
Format: Preprint
Published: 2022
Subjects:
Online Access:https://arxiv.org/abs/2211.01720
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author Zagalo, Kevin
Bar-Hen, Avner
author_facet Zagalo, Kevin
Bar-Hen, Avner
contents 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 \cite{zagalo2022} 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.
format Preprint
id arxiv_https___arxiv_org_abs_2211_01720
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Response time central-limit and failure rate estimation for stationary periodic rate monotonic real-time systems
Zagalo, Kevin
Bar-Hen, Avner
Systems and Control
Statistics Theory
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 \cite{zagalo2022} 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.
title Response time central-limit and failure rate estimation for stationary periodic rate monotonic real-time systems
topic Systems and Control
Statistics Theory
url https://arxiv.org/abs/2211.01720