Bound Computation of Dependability and Performance Measures
Bound Computation of Dependability and Performance Measures
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可靠性和性能测量的约束计算
DOI：
10.1109/12.926156
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发表时间：
2001
期刊：
影响因子：
--
通讯作者：
G. Rubino
中科院分区：
文献类型：
--
作者：
S. Mahévas;G. Rubino
我们提出了一种新的方法来获得由大型马尔可夫模型建模的复杂系统的可信性、性能或可执行性度量的界。它扩展了以前发表的技术，主要设计为只分析可靠性度量，并在更严格的条件下工作。我们的方法允许我们在某些情况下获得性能度量的严格界限，特别是在具有无限状态空间的模型上。我们用一些解析难解的开放排队网络以及大的可信性模型来说明该方法。
We propose a new method to obtain bounds of dependability, performance or performability measures concerning complex systems modeled by a large Markov model. It extends previously published techniques mainly designed to the analysis of dependability measures only and working under more restrictive conditions. Our approach allows us to obtain tight bounds of performance measures on certain cases and, in particular, on models having an infinite state space. We illustrate the method with some analytically intractable open queuing networks, as well as with large dependability models.