A Congestion Control Method for Complex Communication Network Nodes Based on Hybrid Neural Networks
Conventional node congestion control methods for complex communication networks are based on reducing the node operating load,and the congestion control function increases the network load,thus affecting the network communication effect.Therefore,the design of complex communication network node congestion control method based on hybrid neural network.Generate a virtual queue of complex communication network nodes,and queue up in the free buffer space of the virtual queue when the packet arrives to avoid the network node congestion problem,and deploy the communication network node congestion control structure based on hybrid neural network to equalize the network resources as a starting point,and divide the coverage area of the network nodes'equivalent perceptual radius,so as to achieve the purpose of node congestion control.Comparison experiments are used to verify that the method has a better congestion control effect and can be applied in real life.
hybrid neural networkcomplex communication networksnode congestion
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