A Multi-Objective Grouping Genetic Algorithm for Server Consolidation in Cloud Data Centers

As the demand for cloud computing services has increased continuously, the number of cloud service providers and cloud applications are increasing dramatically. This has resulted in a significant increase in data center energy consumption. One of the most well-known ways to improve the efficiency of data centers is server consolidation. In our recent study on server consolidation, we presented a grouping genetic algorithm for a single objective that is minimization of the energy consumption in a data center. In order to enhance the performance of the grouping genetic algorithm, this paper presents a multi-objective grouping genetic algorithm for a multi-objective, including minimizing both the energy consumption and resource wastage. The optimal solution for the multi-objective grouping genetic algorithm is determined by a fitness function that considers the two objectives with a trade-off between each objective. The results from the experiments show that the multi-objective grouping genetic algorithm performs well in terms of the resource wastage and number of active physical machines in the data center and is scalable to the number of virtual machines and physical machines.