The invention discloses an
intelligent network congestion control method based on
frequency domain feature analysis and dynamic
weight adjustment, which comprises the following steps: acquiring network round-trip time RTT and
queue length, and calculating a
jitter value; dFT conversion is performed on the
jitter value into a
frequency domain, and then a high-frequency energy ratio is calculated. And constructing a
state vector, and performing real-time network state
estimation on the
state vector based on a Kalman filtering model to obtain a state
estimation value of the network. According to the high-frequency energy ratio, the weight of the RTT, the
queue length and the
frequency domain feature is dynamically adjusted, and then the parameters of the
PID controller are adaptively adjusted according to the weight. And finally, a PID
control signal generated by the
PID controller is converted into a sending rate
adjustment action or an
explicit congestion notification, so that
network congestion is inhibited in real time. According to the method, the performance of the
data center network in a high-load and
complex network environment can be remarkably improved, the
delay is reduced, the
throughput is improved, data
packet loss is avoided, and the self-adaptive capability of the network is enhanced.