A Compositional Semantics for Stochastic Reo Connectors

In this paper we present a compositional semantics for the channel-based coordination language Reo which 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.Comment: In Proceedings FOCLASA 2010, arXiv:1007.499

A Compositional Semantics for Stochastic Reo Connectors

In this paper we present a compositional semantics for the channel-based coordination language Reo which 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. As a case study, we are currentl

From coordination to stochastic models of QoS

Reo is a channel-based coordination model whose operational semantics is given by Constraint Automata (CA). Quantitative Constraint Automat

Quantitative analysis of reo- based service coordination

Quality of Service analysis of composed software systems is an active research area, with the goal of evaluating and improving performance and resource allocation in serviceoriented applications, namely, in the glue code –coordination layer– of such systems. Stochastic Reo offers constructs for service coordination and allows the specification of stochastic values for channels. But its state-of-the-art semantic models fail in several (important) ways. In this paper, we will see how Interactive Markov chains (IMC), proposed as astochastic compositional model of concurrency, can be effectively used to serve as a compositional semantic model for Stochastic Reo. Treating IMC as a direct semantic model, gives rise to more faithful models and has obvious efficiency advantages. Moreover, tool support that exists for IMC is made available, without significant effort, to verify and reason about the coordination layer modelled as Reo connectors.(undefined

Stochastic models for quality of service of component connectors

The intensifying need for scalable software has motivated modular development and using systems distributed over networks to implement large-scale applications. In Service-oriented Computing, distributed services are composed to provide large-scale services with a specific functionality. In this way, reusability of existing services can be increased. However, due to the heterogeneity of distributed software systems, software composition is not easy and requires additional mechanisms to impose some form of a coordination on a distributed software system. Besides functional correctness, a composed service must satisfy various quantitative requirements for its clients, which are generically called its quality of service (QoS). Particularly, it is tricky to obtain the overall QoS of a composed service even if the QoS information of its constituent distributed services is given. In this thesis, we propose Stochastic Reo to specify software composition with QoS aspects and its compositional semantic models. They are also used as intermediate models to generate their corresponding stochastic models for practical analysis. Based on this, we have implemented the tool Reo2MC. Using Reo2MC, we have modeled and analyzed an industrial software, the ASK system. Its analysis results provided the best cost-effective resource utilization and some suggestions to improve the performance of the system.UBL - phd migration 201

An enhanced model for stochastic coordination

Publicado em "Proceedings of the First International Workshop on Formal Methods for and on the Cloud, iFMCloud@IFM 2016, Reykjavik, Iceland, 4th June 2016"Applications developed over the cloud coordinate several, often anonymous, computational resources, distributed over different execution nodes, within flexible architectures. Coordination models able to represent quantitative data provide a powerful basis for their analysis and validation. This paper extends IMCreo, a semantic model for Stochastic reo based on interactive Markov chains, to enhance its scalability, by regarding each channel and node, as well as interface components, as independent stochastic processes that may (or may not) synchronise with the rest of the coordination circuit.Luis S. Barbosa is supported by grant SFRH/BSAB/113890/2015 from FCT, the Portuguese Foundation for Science and Tecnhology. This research is financed by the ERDF COMPETE 2020 Programme within project POCI-01-0145-FEDER-00696, and by National Funds through FCT as part of project UID/EEA/50014/2013

A specification language for Reo connectors

Recent approaches to component-based software engineering employ coordinating connectors to compose components into software systems. Reo is a model of component coordination, wherein complex connectors are constructed by composing various type

Automata for context-dependent connectors

Recent approaches to component-based software engineering employ coordinating connectors to compose components into software systems. For maximum flexibility and reuse, such connectors can themselves be composed, resulting in an expressive calculus of connectors whose semantics encompasses complex combinations of synchronisation, mutual exclusion, non-deterministic choice and state-dependent behaviour. A more expressive notion of connector includes also context-dependent behaviour, namely, whenever the choices the connector can take change non-monotonically as the context, given by the pending activity on its ports, changes. Context dependency can express notions of priority and inhibition. Capturing context-dependent behaviour in formal models is non-trivial, as it is unclear how to propagate context in- formation through composition. In this paper we present an intuitive automata-based formal model of context-dependent connectors, and argue that it is superior to previous attempts at such a model for the coordination language Reo

From Coordination to Stochastic Models of QoS

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 qua