In order to save the energy consumption in cloud data center, some greedy algorithms-based Virtual Machine (VM) migration strategies were proposed. In these strategies, the virtual migration process was divided into physical host status detection, virtual machine selection and virtual machine placement, and the greedy algorithm was adopted in the process of virtual selection and virtual placement respectively. The three proposed migration strategies were:Minimum Host Utilization selection, Maximum Host Utilization placement (MinMax_Host_Utilization); Maximum Host Power Usage selection, Minimum Host Power Usage placement (MaxMin_Host_Power_Usage); Minimum Host MIPS selection, Maximum Host MIPS placement (MinMax_Host_MIPS). The maximum or minimum thresholds were set for the processor utilization efficency, the energy consumption and the processor computing power of physical host. According to the principle of greedy algorithm, the virtual machines with indicators higher or lower than the thresholds should be migrated. With CloudSim as the simulated cloud data center, the test results show that compared with the static threshold and median absolute deviation migration strategies existing in CloudSim, the proposed strategies have the total energy consumption reduced by 15%, the virtual machine migration number decreased by 60%, and the average SLA violation rate lowered about 5%.