A feature-based approach to system deployment and adaptation

Building large scale systems involves many design decisions, both at specification and implementation levels. This is due to numerous variants in the description of the task to achieve and its execution context as well as in the assembly of software components. We have modeled variability for large scale systems using feature diagrams, a formalism well suited for modeling variablility. These models are built with a clear separation of concerns between specification and implementation aspects. They are used at design and deployment time as well as at execution time. Our test application domain is video surveillance systems, from a software engineering perspective. These are good candidates to put model driven engineering to the test, because of the huge variability in both the surveillance tasks and the video analysis algorithms. They are also dynamically adaptive systems, thus suitable for models at run time approaches. We propose techniques and tools to define the models, to operate on them, and to transform specification requirements into an effective implementation of a processing chain. We also define a run time architecture to integrate models into the adaptation loop.