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Designing data-centers that provide an acceptable costperformance ratio is challenging. Generally, a wide spectrum of components must be previously analyzed, such as the kind of applications to be executed in the data-center, computing/storage requirements and the network topology, among others. Since each one of these components has a direct impact on the overall system performance, the design process is complex and difficult, which usually requires the intervention of an expert. We propose a model-based approach to design datacenters. For this purpose, we have created a meta-model that describes the structure of data-center models. Then, a set of expert rules can be used to detect sub-optimal configurations, and (in some cases) correct the design. Datacenter models can be simulated, to assess their performance and scalability, for which we use a code generator into the SIMCAN tool. We have implemented our approach as an Eclipse plugin, and illustrate the usefulness of some expert rules by showing the efficiency and scalability gains of the optimized model with respect to the original one.

MAGICIAN: Model-based design for optimizing the configuration of data-centers