Model-driven Automated Deployment of Large-scale CPS Co-simulations in the Cloud

With increasing advances in Internet-enabled devices, large cyber-physical systems (CPS) are being realized by integrating several sub-systems together. Analyzing and reasoning different properties of such CPS requires co-simulations by composing individual and heterogeneous simulators, each of which addresses only certain aspects of the CPS. Often these co-simulations are realized as point solutions or composed in an ad hoc manner, which makes it hard to reuse, maintain and evolve these co-simulations. Although our prior work on a modelbased framework called Command and Control Wind Tunnel (C2WT) supports distributed co-simulations, many challenges remain unresolved. For instance, evaluating these complex CPSs requires large amount of computational and I/O resources for which the cloud is an attractive option yet there is a general lack of scientific approaches to deploy co-simulations in the cloud. In this context, the key challenges include (i) rapid provisioning and de-provisioning of experimental resources in the cloud for different co-simulation workloads, (ii) simulating incompatibility and resource violations, (iii) reliable execution of co-simulation experiments, and (iv) reproducible experiments. Our solution builds upon the C2WT heterogeneous simulation integration technology and leverages the Docker container technology to provide a model-driven integrated tool-suite for specifying experiment and resource requirements, and deploying repeatable cloudscale experiments. In this work, we present the core concepts and architecture of our framework, and provide a summary of our current work in addressing these challenges.