Cognitive Networks Congestion Prediction Method Based on Bayesian Networks
With the rapid expanding of network scale and complexity, the occurrence of network congestion has been increased as well. To avoid network congestion, the authors proposed a cognitive networks congestion prediction method based on Bayesian Networks. With the help of Bayesian Networks the authors can predict the network parameters, decide actively, adjust the protocol stack parameters and optimize network performance according to the known protocol stack parameters and the current network state. The simulation results show that the method can make prediction of congestion efficiently and effectively, predicting and avoiding network congestion caused by complexity and volatility of the network.