Abstract: In order to improve the dynamic transmission capability of lightweight communication networks, a dynamic routing algorithm for lightweight communication networks based on convolutional neural networks is proposed. Based on the establishment of a lightweight communication network dynamic node deployment model, a network dynamic routing detection model is established through the network node rotation scheduling method. Then the distributed conversion protocol is used to reorganize the lightweight communication network dynamic routing feature space structure. After establishing the node multiple coverage scheduling model, the sensor information fusion tracking method is used to detect the network dynamic routing feature. Based on this, the routing forwarding and adaptive control protocol are established, and the node traversal method is used to control the channel balance of the lightweight communication network. Under the constraint of optimal node communication coverage, the lightweight communication network dynamic routing scheduling is realized, and then the convolutional neural network is used to carry out the convergence adjustment of the dynamic routing control of the lightweight communication network. The simulation results show that the channel interference can be effectively suppressed and the network throughput can be improved after adopting this method, which proves that the node forwarding ability of dynamic routing in the lightweight communication network is better.

Key words: convolutional neural network, lightweight communication network, dynamic routing, control protocol