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


Abstract:

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.

Año de publicación:

2017

Keywords:

    Fuente:

    scopusscopus

    Tipo de documento:

    Conference Object

    Estado:

    Acceso abierto

    Áreas de conocimiento:

    • Computación en la nube
    • Ciencias de la computación

    Áreas temáticas de Dewey:

    • Ciencias de la computación
    • Producción
    • Física aplicada
    Procesado con IAProcesado con IA

    Objetivos de Desarrollo Sostenible:

    • ODS 9: Industria, innovación e infraestructura
    • ODS 12: Producción y consumo responsables
    • ODS 8: Trabajo decente y crecimiento económico
    Procesado con IAProcesado con IA