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A fault-tolerant dynamic scheduling algorithm for multiprocessor real-time systems and its analysis

机译:多处理器实时系统的容错动态调度算法及其分析

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Many time-critical applications require dynamic scheduling with predictable performance. Tasks corresponding to these applications have deadlines to be met despite the presence of faults. In this paper, we propose an algorithm to dynamically schedule arriving real-time tasks with resource and fault-tolerant requirements on to multiprocessor systems. The tasks are assumed to be nonpreemptable and each task has two copies (versions) which are mutually excluded in space, as well as in time in the schedule, to handle permanent processor failures and to obtain better performance, respectively. Our algorithm can tolerate more than one fault at a time, and employs performance improving techniques such as 1) distance concept which decides the relative position of the two copies of a task in the task queue, 2) flexible backup overloading, which introduces a trade-off between degree of fault tolerance and performance, and 3) resource reclaiming, which reclaims resources both from deallocated backups and early completing tasks. We quantify, through simulation studies, the effectiveness of each of these techniques in improving the guarantee ratio, which is defined as the percentage of total tasks, arrived in the system, whose deadlines are met. Also, we compare through simulation studies the performance our algorithm with a best known algorithm for the problem, and show analytically the importance of distance parameter in fault-tolerant dynamic scheduling in multiprocessor real-time systems.
机译:许多时间紧迫的应用程序都需要具有可预测性能的动态调度。尽管存在故障,但与这些应用程序相对应的任务仍要满足最后期限。在本文中,我们提出了一种将具有资源和容错要求的实时到达任务动态调度到多处理器系统的算法。假定这些任务是不可抢占的,并且每个任务有两个副本(版本),它们在空间上以及时间表中的时间上都互斥,以分别处理永久性处理器故障并获得更好的性能。我们的算法一次可以容忍一个以上的故障,并采用了性能改进技术,例如1)距离概念,该概念确定任务的两个副本在任务队列中的相对位置; 2)灵活的备份超载,这引入了交易-在容错程度和性能之间切换;以及3)资源回收,该资源回收已释放的备份和早期完成的任务中的资源。通过模拟研究,我们量化了每种技术在提高保证率方面的有效性,该保证率定义为按时完成的到达系统的总任务的百分比。此外,我们通过仿真研究比较了该算法与该问题的最佳算法的性能,并分析了距离参数在多处理器实时系统的容错动态调度中的重要性。

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