Today, the variety of cloud data centers that provide large-scale Internet services is enlarging rapidly. While the operating cost of these centers also increases due to energy consumption. The key challenge of energy efficiency in the cloud is to reduce service level agreement violations and resource usage. In the meantime, the idea of virtualization uses the migration technology of virtual machines to consolidate the server workload and improve the energy consumption of cloud data centers. Virtual machine integration prevents the low efficiency of storage equipment and servers and their large space occupation. Virtual machine selection is one of the sub-problems in the technique of dynamic merging of virtual machines, which selects the best candidate virtual machine from among the virtual machines that are loaded on the host for migration. This research looks at the methods of solving the problem of choosing virtual machines for migration, which has improved energy consumption. Remarkably, the investigation of ant colony optimization algorithms for choosing a virtual machine help to choose a virtual machine in cloud environments, reduce the energy consumption costs and more than a few migrations of virtual machines and raise the level of customer satisfaction.