网络稳定多参数控制模型仿真

Network Stability Multi-Parameter Control Model And Simulation

在保持网络的稳定性、提高网络数据的传输效率问题的研究中,利用传统算法保持网络的稳定,只能解决单一链路堵塞的问题,一旦多用户同时使用,网络将会导致网络稳定性降低。为解决上述问题,提出一种采用神经网络的网络稳定多参数控制方法。将网络中多节点和多链路的选择问题看作多且标优化问题,将与链路连通性有关的参数作为多目标函数中的控制参数,在保持网络稳定时将上述参数作为约束条件进行控制,利用三层前馈神经网络构建保持网络稳定性的神经网络模型,提高了网络的稳定性。实验结果表明,利用改进算法能够使网络在大负载的情况下保持较高的稳定性。

Maintain network stability for the improvement of the network data transmission efficiency is of great importance. Maintain network stability in the process of using the traditional algorithm, can solve the problem of single link congestion, once more users at the same time using the network will lead to reduce the network stability. For this, put forward a kind of network more stable parameter control method based on neural network. Will be more nodes and links in the network selection problem as a multi-objective optimization problem, the parameters related to the link connectivity as control parameter in the multi-objective function, in keeping the network stability to control the above parameters as the constraint condition, using the three-layer feed-forward neural network to keep the sta- bility of the neural network model was constructed and improved the stability of the network. The experimental results show that the improved algorithm can keep the network under the condition of the large load of high stability.