Industrial IoT Fog Node Adaptation in Complex Network Environment

It has become a trend to deploy a large number of edge devices in an industrial IoT environment to build an edge network architecture. More and more factories are choosing this method to increase production efficiency. The advantage of the edge network is to improve the anti-interference ability of the real-time system by utilizing the fast response capability of the fog node. But the limited resources of the fog node are not enough to conFigure all the required services. Adaptive configuration must track changes in demand for industrial equipment, minimize latency, and ensure system stability while meeting constraints and constraints. This paper examines how to adapt fog node configurations under harsh and complex network conditions to ensure system stability, at the same time, the power shortage and communication constraints of the edge devices in actual production are also considered. Meanwhile, we have improved a distributed stochastic optimization algorithm based on parallel Gibbs sampling method to make it more adaptable to the harsh and complex communication environment. Simulation results show that the algorithm can balance the energy shortage of edge devices in a harsh and complex network communication environment, while ensuring good system performance and stability.