From Coordination to Stochastic Models of QoS
From Coordination to Stochastic Models of QoS
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DOI：
10.1007/978-3-642-02053-7_14
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发表时间：
2009-03
期刊：
影响因子：
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通讯作者：
F. Arbab;Tom Chothia;R. Mei;S. Meng;Young-Joo Moon;Chrétien Verhoef
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文献类型：
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作者：
F. Arbab;Tom Chothia;R. Mei;S. Meng;Young-Joo Moon;Chrétien Verhoef
Reo是一个基于通道的协调模型，其操作语义由约束自动机（CA）给出。定量约束自动机扩展了CA（因此，Reo）的定量模型，以捕获系统行为的非功能性方面，如延迟，成本，资源需求和消耗，这取决于系统的内部细节。然而，系统的性能不仅取决于其内部细节，还取决于它在环境中的使用方式，例如由I/O请求到达的频率和分布所确定。在本文中，我们提出了定量意向自动机（QIA），CA的扩展，允许将系统的环境对其性能的影响。此外，我们将QIA翻译成连续时间马尔可夫链（CTMCs），这使我们能够应用现有的CTMC工具和技术进行QIA和Reo电路的性能分析。
Reo is a channel-based coordination model whose operational semantics is given by Constraint Automata (CA). Quantitative Constraint Automata extend CA (and hence, Reo) with quantitative models to capture such non-functional aspects of a system’s behaviour as delays, costs, resource needs and consumption, that depend on the internal details of the system. However, the performance of a system can crucially depend not only on its internal details, but also on how it is used in an environment, as determined for instance by the frequencies and distributions of the arrivals of I/O requests. In this paper we propose Quantitative Intentional Automata (QIA), an extension of CA that allow incorporating the influence of a system’s environment on its performance. Moreover, we show the translation of QIA into Continuous-Time Markov Chains (CTMCs), which allows us to apply existing CTMC tools and techniques for performance analysis of QIA and Reo circuits.