2009 | OriginalPaper | Chapter
From Coordination to Stochastic Models of QoS
Authors : Farhad Arbab, Tom Chothia, Rob van der Mei, Sun Meng, YoungJoo Moon, Chrétien Verhoef
Published in: Coordination Models and Languages
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
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.