Efficient and robust probabilistic guarantees for real-time tasks
Efficient and robust probabilistic guarantees for real-time tasks
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DOI：
10.1016/j.jss.2011.12.042
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发表时间：
2012-05
期刊：
影响因子：
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通讯作者：
Luca Abeni;Nicola Manica;L. Palopoli
中科院分区：
文献类型：
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作者：
Luca Abeni;Nicola Manica;L. Palopoli
本文提出了一种新的方法，通过资源预留调度的任务提供概率实时保证。通过提高概率计算的效率和鲁棒性，扩展了先前关于基于预留的调度器的概率分析的工作。通过考虑计算时间分布的可能不完整的知识（这在实际应用中是典型的）来提高鲁棒性。所提出的方法计算一个保守的约束错过最后期限的概率，基于执行时间的概率分布和任务的到达时间间隔的知识。在本文中，这样的界限计算在现实的情况下，比较它与模拟结果和精确计算的截止日期错过概率（没有悲观的界限）。最后，执行时间分布的不完全知识的影响进行了评估。
This paper presents a new method for providing probabilistic real-time guarantees to tasks scheduled through resource reservations. Previous work on probabilistic analysis of reservation-based schedulers is extended by improving the efficiency and robustness of the probability computation. Robustness is improved by accounting for a possibly incomplete knowledge of the distribution of the computation times (which is typical in realistic applications). The proposed approach computes a conservative bound for the probability of missing deadlines, based on the knowledge of the probability distributions of the execution times and of the inter-arrival times of the tasks. In this paper, such a bound is computed in realistic situations, comparing it with simulative results and with the exact computation of deadline miss probabilities (without pessimistic bounds). Finally, the impact of the incomplete knowledge of the execution times distribution is evaluated.