云计算网络下的网络抗毁性估计模型仿真

发布时间：2018-10-15 12:21

【摘要】：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。
[Abstract]:Whether cloud computing network can run effectively has a very important relationship with network survivability. Based on cloud computing network, the load capacity model of cloud computing network is constructed by analyzing the invulnerability index. According to the influence of different density nodes and different capacity on cloud computing network survivability, the network capacity density is adjusted to obtain the best cloud computing network survivability. Through the simulation experiment, the improved algorithm is compared with the traditional neural network method and fuzzy probability method (, GM (1N). Experiments show that the accuracy of the improved algorithm for cloud computing network damage estimation is the highest 0.96, and the highest number of connected nodes is 99. The improved algorithm is superior to the other three algorithms in network applicability, damage speed and damage degree. The security of cloud computing network data transmission process is guaranteed.
【作者单位】：陕西警官职业学院;
【基金】：国家自然科学基金青年项目:大数据背景下的特征选择算法在数据分析中的应用(F030504) 陕西省教育厅课题:基于云计算的大数据安全的研究(SGH12532)
【分类号】：TP393.08

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