Contribution in private cloud computing development based on study and KPI analysis

Abstract

The preset paper describes a contributes in the implementation of private Cloud Computing. Exhaustive study made validates Cloud environment creation and successful deployed Solution Configuration choice. Related solution ensures a good investment that reduces energy costs of the data center, minimizes network traffic cost proven as an NP-hard problem. In addition, each virtual machine (VsM) depends on energy within the data center. Used genetic algorithm allows the emergence of new generations, the use of Tabu search algorithm demonstrates a divergence state, however an identification technique, based on a hybrid algorithm, ensures which optimized virtual machine.