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.

A Framework for Modeling Cloud Infrastructures and User Interactions

“…Thus, we have researched several relevant current papers on this subject and well-known simulation tools in order to gather the different aspects of the cloud and their clients that should be modeled. The parameters to design a data-center were extracted from the cloud simulators GreenCloud [15] and iCanCloud [7], and from MAGICIAN [6], which is a model-based approach to the design of data-centers. CloudSim [4], [5] supplies an accurate model to represent VMs and to design resource allocation policies, which have been adapted in designing our proposed profile.…”