A new physical resource utilization thresholds management strategy called RUT-MS for cloud data centers is proposed in this paper. In RUT-MS， the virtual machine migration process is divided into five steps： Overloaded host status detection， virtual machine selection， the first virtual machine placement， under-loaded host status detection and the second virtual machine placement phases. In overloading host detection， RUT-MS uses an iterative weighted linear regression method to determine two utilization thresholds so that the performance degradation is avoided. Maximum power reduction policy （MPR） is adopted in virtual machine selection phase. A vector magnitude squared of multiple dimension resources is used to decide the low resource utilization thresholds and switch them to a power saving mode. Finally， RUT-MS is evaluated using CloudSim with real-world workload data. Simulation results show that RUT-MS can reduce the energy cost incurred on the system due to migration. The reduced number of virtual machine migrations and improved energy-efficiency are also obtained in our test. Moreover， the service level agreement （SLA） violation and SLA for energy united metrics are also good.