In view of the high energy consumption of data centers, the random dynamics of application task load, and the low latency requirements of users for applications, on the basis of the fog computing system architecture, a container integration method based on advantage actor-critic (A2C) algorithm is proposed to minimize energy consumption and average response time. The method uses checkpoint/recovery technology to migrate containers in real time to achieve resource integration. An end-to-end decision model from data center system state to container integration is constructed, and an adaptive multi-objective reward function is proposed. The gradient-based backpropagation algorithm is used to accelerate the convergence speed of the decision model. Simulation results based on real task load datasets show that the proposed method can effectively reduce energy consumption while ensuring service quality.