Efficient Encodings for Scalable Exploration of Cyber-Physical System Architectures

We present a methodology for scalable exploration of cyber-physical system architectures. We propose a mathematical formulation of the architecture exploration problem as an optimized mapping problem that includes joint selection of system topologies and components taken from predefined libraries. Using a graph-based representation of an architecture, we introduce novel compact encodings of mapping constraints and path constraints that significantly improve the scalability of the formulation. We use the new encodings to instantiate design requirements, such as interconnection, routing, timing, and energy constraints, on the architecture model. We implement our methods in an extensible architecture exploration toolbox, and provide a pattern-based language for formal, yet flexible, requirement specification. Numerical evaluations on a set of design problems from wireless sensor networks, reconfigurable manufacturing systems, and electrical power systems demonstrate the effectiveness of our approach.