Foundations for Continuous Time Hierarchical Co-simulation

Complex systems have to decomposed into sub-systems which are developed by specialized teams. Modeling and simulation techniques help each team achieve a locally optimal solution but they fail to help all teams achieve a globally optimal solution. This is due to each team having its own models made in its own tools, and external suppliers having intellectual property. The result is that it is difficult to simulate the coupled system. Co-simulation is proposed as a way to enable such simulation. Simulators communicate and collaborate as black boxes. The technique has been used in a number of domains improving the overall cost of engineered systems. In these use cases, a minimum common denominator is assumed for the capabilities of simulators. Leveraging the optional capabilities of simulators improves the performance/accuracy of a co-simulation, but the number of decisions the orchestration mechanism has to make grows exponentially. Different, conflicting concerns have to be addressed in an optimal way. We propose a way to deal with each concern independently and possibly reuse existing orchestration algorithms that perform better with respect to the conflicting concerns. Our approach leverages Model Driven Development techniques to process a co-simulation scenario into a canonical/trivial version, where fewer decisions remain to be made. Along the process, conflicting concerns will be addressed as an optimization problem, and an appropriate cost function identified. If successful, the result of this research allows co-simulation scenarios that may offer real-time guarantees, bounds in the maximum error made, or packet size in the communication between simulators.