The invention discloses a group
virtual machine scheduling policy for a
cloud computing environment. The policy comprises the following steps of S1, establishing a feasible decision space of
virtual machine scheduling; S2, minimizing total flow of a network where group virtual machines are located, and establishing an objective function for optimizing the total flow of the network; S3, minimizinga maximum link
utilization rate in the network, and establishing an objective function for optimizing the maximum link
utilization rate; and S4, establishing an overall objective function, and solvingthe overall objective function in combination with an
ant colony
algorithm and a
simulated annealing algorithm to obtain an optimal solution of the function and mapping relationships between the virtual machines and a physical
machine. Under the condition of fully considering
resource constraints, the control of the total flow of the network and the balance of flow distribution on a network linkare defined as a combination
optimization problem, and solving is performed in combination with the
ant colony
algorithm and the
simulated annealing algorithm. According to the scheduling policy provided by the invention, the performance of the network where the group virtual machines are located can be better optimized; the congestion is reduced; and the
service quality of users is effectively improved.