固定周期速率单调实时系统的响应时间中心极限与失效率估计
Response time central-limit and failure rate estimation for stationary periodic rate monotonic real-time systems
AI总结：
针对速率单调实时系统，利用响应时间中心极限和逆高斯混合分布近似，通过重参数化与EM算法估计失效率，仿真验证方法有效性。
摘要：
实时系统由一组任务、调度策略和系统架构组成，所有部分都受时序约束。许多日常嵌入式系统，如飞机、汽车、火车和空间探测器中的设备，都作为实时系统运行。为了确保安全的失效率，响应时间（执行任务所需的时间）必须是有界的。速率单调实时系统根据任务的到达率对任务进行优先级排序。本文关注使用\cite{zagalo2022}中构建的响应时间中心极限及其通过逆高斯混合分布近似的分布。通过适当的逆高斯分布重参数化和改进的期望最大化算法，估计分布参数及其相关的失效率。大量仿真表明，该方法非常适合失效率的近似。我们讨论了将该方法扩展到适用于实时系统的卡方独立性检验。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
