A compositional model to reason about end-to-end QoS in Stochastic Reo connectors

In this paper, we present a compositional semantics for the channel-based coordination language Reo that enables the analysis of quality of service (QoS) properties of service compositions. For this purpose, we annotate Reo channels with stochastic delay rates and explicitly model data-arrival rates at the boundary of a connector, to capture its interaction with the services that comprise its environment. We propose Stochastic Reo Automata as an extension of Reo automata, in order to compositionally derive a QoS-aware semantics for Reo. We further present a translation of Stochastic Reo Automata to Continuous-Time Markov Chains (CTMCs). This translation enables us to use third-party CTMC verification tools to do an end-to-end performance analysis of service compositions. In addition, we discuss to what extent Interactive Markov Chains (IMCs) can serve as an alternative semantic model for Stochastic Reo. We show that the semantics of Stochastic Reo cannot be specified compositionally using the product operator provided by IMCs.

► We introduce a compositional semantic model for stochastic Reo.
► The model is translated into Continuous-Time Markov Chains for stochastic analysis.
► As an industrial application of our approach, we model parts of the ASK system.
► As an alternative semantic model for Reo, Interactive Markov Chains are discussed.