Probabilistic Chemical Abstract Machine and the Expressiveness of Linda Languages

The Chemical Abstract Machine of Berry and Boudol provides a commonly accepted, uniform framework for describing the operational semantics of various process calculi and languages, such as for example CCS, the pi-calculus and coordination languages like Linda. In its original form the CHAM is purely non-deterministic and thus only describes what reactions are `possible' but not how long it will take (in the average) before a certain reaction takes place or its probability. Such quantitative information is however often vital for ``real world'' applications such as systems biology or performance analysis. We propose a probabilistic version of the CHAM. We then define a linear operator semantics for the probabilistic CHAM which exploits a tensor product representation for distributions over possible solutions. Based on this we propose a novel approach towards comparing the expressive power of different calculi via their encoding in the probabilistic CHAM. We illustrate our approach by comparing the expressiveness of various Linda Languages

Logic Fragments: A Coordination Model Based on Logic Inference

Part 1: Tuple-Based CoordinationInternational audienceChemical-based coordination models have proven useful to engineer self-organising and self-adaptive systems. Formal assessment of emergent global behaviours in self-organising systems is still an issue, most of the time emergent properties are being analysed through extensive simulations. This paper aims at integrating logic programs into a chemical-based coordination model in order to engineer self-organising systems as well as assess their emergent properties. Our model is generic and accommodates various logics. By tuning the internal logic language we can tackle and solve coordination problems in a rigorous way, without renouncing to important engineering properties such as compactness, modularity and reusability of code. This paper discusses our logic-based coordination model and shows how to engineer and verify a simple pattern detection example and a gradient-chemotaxis example

A mathematical semantics for architectural connectors

A mathematical semantics is proposed for the notion of architectural connector, in the style defined by Allen and Garlan, that builds on Goguen’s categorical approach to General Systems Theory and other algebraic approaches to specification, concurrency, and parallel program design. This semantics is, essentially, ADL-independent, setting up criteria against which formalisms can be evaluated according to the support that they provide for architectural design. In particular, it clarifies the role that the separation between computation and coordination plays in supporting architecture-driven approaches to software construction and evolution. It also leads to useful generalisations of the notion of connector, namely through the use of multiple formalisms in the definition of the glue and the roles, and their instantiations with programs or system components that can be implemented in different languages or correspond to "real-world" components

Self-organising Pervasive Ecosystems: A Crowd Evacuation Example

The dynamics of pervasive ecosystems are typically highly unpredictable, and therefore self-organising approaches are often exploited to make their applications resilient to changes and failures. The SAPERE approach we illustrate in this paper aims at addressing this issue by taking inspiration from natural ecosystems, which are regulated by a limited set of "laws" evolving the population of individuals in a self-organising way. Analogously, in our approach, a set of so-called eco-laws coordinate the individuals of the pervasive computing system (humans, devices, signals), in a way that is shown to be expressive enough to model and implement interesting real-life scenarios. We exemplify the proposed framework discussing a crowd evacuation application, tuning and validating it by simulation