Towards Scalable Model Views On Heterogeneous Model Resources

When engineering complex systems, models are used to represent various systems aspects. These models are often heterogeneous in terms of modeling language, provenance, number or scale. They can be notably managed by different persistence frameworks adapted to their nature. As a result, the information relevant to engineers is usually split into several interrelated models. To be useful in practice, these models need to be integrated together to provide global views over the system under study. Model view approaches have been proposed to tackle such an issue. They provide an unification mechanism to combine and query heterogeneous models in a transparent way. These views usually target specific engineering tasks such as system design, monitoring, evolution, etc. In our present context, the MegaM@Rt2 industrially-supported European initiative defines a set of large-scale use cases where model views can be beneficial for tracing runtime and design time data. However, existing model view solutions mostly rely on in-memory constructs and low-level modeling APIs that have not been designed to scale in the context of large models stored in different kinds of sources. This paper presents the current status of our work towards a general solution to efficiently support scalable model views on heterogeneous model resources. It describes our integration approach between model view and model persistence frameworks. This notably implies the refinement of the view framework for the construction of large views from multiple model storage solutions. This also requires to study how parts of queries can be computed on the contributing models rather than on the view. Our solution has been benchmarked on a practical large-scale use case from the MegaM@Rt2 project, implementing a runtime - design time feedback loop. The corresponding EMF-based tooling support and modeling resources are fully available online.