Abstrakt
Smart cyber-physical systems (sCPS) is a growing research field focused on scenarios where a set of autonomous software-hardware entities (components) is cooperating via network communication to achieve a type of swarm or cloud intelligence. Typically the components' cooperation is designed at a low level of abstraction and their behavior validated via simulations.
As a remedy, a declarative language capable of specifying high-level component ensembles has been proposed in recent work. By capturing component functionality and the cooperation constraints, a specification serves both for generating platform-specific implementation and as a model@run.time to support self-adaption via dynamic formation of ensembles.
However, for a particular specification, multiple possible architectural configurations exist with various impact on the system. Given their typically large number, we select the best one via an SMT solver.
In this paper, we show that scalability of such approach can be suppor ted by exploiting the effect of locality in component cooperation and by hoisting specific domain knowledge to the level of architecture.