Industrial IoT Fog Node Adaptive Configuration In Complex Network

It has become a trend to deploy a large number of edge devices in an industrial IoT environment to build an edge network architecture.The advantage of the edge network is to improve the anti-interference ability of the real-time system and reduce the overall system service delay by utilizing the fast response capabilities of the fog nodes.But the limited resources of fog nodes are not enough to configure the services necessary for all sensor nodes.The adaptive configuration of fog nodes must track changes in industrial equipment requirements,minimize delays,and ensure system stability while meeting constraints.This article studies how fog nodes can be adaptively configured to ensure system stability and low latency under harsh and complex network conditions.At the same time,we also considered the insufficient power supply constraints and communication constraints of fog nodes at the edge equipment in actual industrial production.After that,we improved a distributed stochastic optimization algorithm based on the parallel Gibbs sampling method to make it more suitable for harsh and complex network communication environments,and added a simulated annealing strategy to ensure convergence.Simulation results show that the algorithm can balance the energy shortage constraints and system delay requirements of fog nodes in a harsh and complex network communication environment,while ensuring the stability of the system.