Model Level Integrated Simulation Architecture for Collaborative Development (CAMLI)

CAMLI provides Advanced Modeling and Simulation Architecture Framework that enables development teams to integrate algorithmic models into a simulation solely through a collaboration layer/interface and software controls. CAMLI architecture addresses: ease of model integration, model composability, execution speed, and ease of data collection and retrieval. To achieve these objectives, the Discrete Event System Specification (DEVS) modeling and simulation formalism provides the theoretical and practical basis to manage whole ecosystems of related models through a simulation architecture framework. RTSync's MS4 Me simulation tools are extended to support the integration of algorithmic models through interfaces. Work in Phase I sponsored by MDA SBIR program successfully demonstrated the utility of incorporating algorithmic models into DEVS models using a realistic ballistic missile case study. In Phase II, we design the overall architecture to support algorithmic model composition, reuse, search, and related features. More particularly, we design and implement a browser that enables users to find algorithmic and other models for compositional reuse, and to support verification and validation of reusable models.

  • Ease of model integration: Adding a new model should not generally require any changes to the simulation architecture software, with all modifications of data structure (e.g. adding additional parameters) accomplished through model meta-data/parameters.
  • Model composability: A team developing a representation of a system or sub-system within the simulation architecture should be able to select needed models from a library of integrated models and build up their respective relationships relative to the representation, to include triggering mechanisms, and association with self and other entities.
  • Speed of execution: Ideally, a simulation constructed with this architecture would execute as fast as a fully integrated simulation using the same algorithmic models.
  • Ease of data collection and retrieval: All representation/entity level state data and any data passed between models should be collectable

  • Composability demonstration using BMDS algorithmic models