TCP Congestion Control on clients and servers is setup to "back off" in these cases in order to ensure that the network remains available for all its users.
TCP拥塞控制就是在这种情况下，通过服务器和客户端的控制“回退”，以确保网络对于其他的所有用户仍然可用。
This paper presents an adaptive congestion control model in ATM networks at the user to network interface by using a diagonal recurrent neural network (DRNN) as an predictor.
提出一种在用户-网络接口处利用对角递归神经网络(DRNN)作为自适应预测器，实现AT M网络自适应拥塞控制的模型。
Supposing the congestion control algorithm is not used in the Internet, the occurrence of congestion collapses can seriously reduce the network performance.
如果不在互联网中使用拥塞控制算法，拥塞崩溃的发生会严重降低网络的性能。
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