Efficient Stochastic Analysis of Real-Time Systems via Random Sampling
Efficient Stochastic Analysis of Real-Time Systems via Random Sampling
复制标题
通过随机采样对实时系统进行高效随机分析
DOI：
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
P. Hladik
中科院分区：
文献类型：
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作者：
Khaled S. Refaat;P. Hladik
提出了一种抢占式优先级驱动调度下实时系统的随机分析方法。其主要思想是通过随机抽样来简化执行时间分布，以降低复杂性。悲观情绪的增加抵消了这一有利影响。然而，与经典的最坏情况确定性分析相比，所提出的分析明显不那么悲观。此外，它还可以根据内存和时间可用性进行调整。因此，建议的方法首次提供了悲观情绪和计算资源之间的关系。测试结果表明，该抽样方法具有较好的实用性和乐观性。
This paper provides a stochastic approach to the analysis of real-time systems under preemptive priority-driven scheduling. The main idea is to simplify the execution time distributions via random sampling to decrease complexity. This beneficial effect is counterbalanced by an increase in pessimism. However, the proposed analysis is significantly less pessimistic than the classical worst-case deterministic analysis. In addition, it could be tuned according to the memory and time availability. Thus, the proposed method provides, for the first time, a relation between pessimism and computational resources. The testing results show the effectiveness of the sampling approach in terms of practicality and optimism.