Service Offloading Algorithm Based on Depth Deterministic Policy Gradient in Fog Computing Environment

In the fog computing environment, in order to solve the problem of large service offload delay in large-scale network, this paper first designs a layered service offload management architecture of the Internet of things in large-scale fog computing environment. Based on the management architecture, four service unloading modes are proposed according to the task characteristics. Secondly, based on the theory of deep deterministic policy gradient (DDPG), a decision model of service unloading based on DDPG is constructed. Finally, aiming at minimizing the service offload delay, a service offload algorithm based on DDPG is proposed. In the experiment, the algorithm is compared with the traditional algorithm, which proves that the algorithm has great advantages in the delay and success rate of service unloading.