云计算网络下的网络抗毁性估计模型仿真

Simulation of network invulnerability estimation model based on cloud computing network

云计算网络能否有效运行与网络抗毁性有非常重要的关系,基于云计算网络,通过分析抗毁性指标进行云计算网络负载容量模型的构建,根据不同密度节点与不同容量对云计算网络抗毁性的影响,对其网络容量密度进行调节,得到最佳云计算网络抗毁性能。并通过仿真实验,将提出的改进算法与传统的神经网络法、模糊概率法、GM(1,N)进行对比。实验表明,改进算法对云计算网络毁伤程度估计准确性最高为0.96,连通节点数目最高为99,改进算法在网络适用性、毁伤速度、毁伤程度三方面均优于其他三种算法,实用性较强,使云计算网络数据传输过程的安全性得到了保证。

The effective operation of the cloud computing network has a crucial relationship with the network invulnerability. On the basis of the cloud computing network, the load capacity model of the cloud computing network was constructed by ana- lyzing the invulnerability indicators. According to the influence of the different density nodes and different capacities on the cloud computing network invulnerability, the network capacity density is adjusted to obtain the best invulnerability of the cloud computing network. The improved algorithm proposed in this paper is compared with the traditional neural network algorithm, fuzzy probability algorithm and GM （ 1, N） algorithm by means of the simulation experiment. The experimental results show that the accuracy of the algorithm to estimate the cloud computing network invulnerability can reach up to 0.96, the maximum quantity of the connection nodes is 99, the algorithm is superior to the other three algorithms in the aspects of network applicability, damage rate and damage degree, has strong practicability, and can guarantee the security of the cloud computing network data in the transmission process.