网络入侵环境下健康节点选择方法设计与仿真

提出一种网络入侵环境下健康节点通信选择算法.针对节点特征建立模糊数学模型,对健康节点选择的成本进行约束,引入粒子群优化算法,结合不确定因素,对参数进行优化,实现健康节点的选择.实验结果表明:与传统的BP神经网络方法相比,改进的网络入侵环境下健康节点通信选择算法提高了健康节点选择的精度,缩短了运行时间,能将入侵后的误差控制在合理的范围内.

Health Design and Simulation of the Node Selection Method in Environment of Network Intrusion

Accurately selectting health node in network intrusion environment can guarantee the normal operation of the network. Fuzzy mathematics model is established based on the node characteristics to constraint the cost of the health node selection. Introducing the particle swarm optimization algorithm combining with the uncertainties to optimize the parameters, and to achieve healthy node selection. The experimental results show that compared with the traditional BP neural network method, the improved network intrusion environment health communication node selection algorithm improved the precision of node selection of health, shorten the operation time. After the invasion, the error can be controlled in a reasonable range.