Complex computational systems — such as pervasive, adaptive, and self-organising ones — typically rely on simple yet expressive coordination mechanisms: this is why coordination models and languages can be exploited as the sources of the essential abstractions and mechanisms to build such systems. While the features of tuple-based models make them well suited for complex system coordination, they lack the probabilistic mechanisms for modelling the stochastic behaviours typically required by adaptivity and self-organisation.
To this end, in this paper we explicitly introduce uniform primitives as a probabilistic specialisation of standard tuple-based coordination primitives, replacing don’t know non-determinism with uniform distribution. We define their semantics and discuss their expressiveness and their impact on system predictability.