大数据消冗技术下虚拟网络聚类特征层次布局算法

Hierarchical Layout Algorithm of Virtual Network Clustering Features Based on Big Data Redundancy Elimination Technology

针对在虚拟网络布局过程中,存在大量重复特征与相关性较少的特征,影响其布局效率的问题,提出了大数据消冗技术下虚拟网络聚类特征层次布局算法。利用加权无向图方式建立虚拟网络图,通过社团划分虚拟网络社团结构,在保持原有特征不变的前提下,最大限度消除虚拟网络聚类特征,得到相关性较大特征;根据库伦力的斥力增加各社团之间距离,采用胡克定律的引力缩小网络节点与中心点之间距离,结合共轭梯度(FR:Flecher-Reeves)算法调整虚拟网络聚类特征层节点的斥力与引力之间关系,实现层次布局算法。实验结果表明,所提算法能更加清晰展现出各社团内部结构特征,且布局用时最短。

In the process of virtual network layout,there are a lot of repetitive features and features with less correlation,which affect the efficiency of its layout.Therefore,a hierarchical layout algorithm of virtual network clustering features under big data redundancy technology is proposed.A weighted undirected graph is used to establish a virtual network graph,and the community structure of the virtual network is divided by communities,so that the clustering characteristics of the virtual network are eliminated to the maximum extent under the premise of keeping the original characteristics unchanged,and the characteristics with high correlation are obtained.According to the repulsion of Coulomb force,the distance between communities is increased,and the distance between network nodes and central points is reduced by the gravity of Hooke's law.Combined with FR(Flecher-Reeves)algorithm,the relationship between repulsion and gravity of virtual network clustering feature layer nodes is adjusted,and the hierarchical layout algorithm is realized.The experimental results show that the proposed algorithm can more clearly show the internal structure characteristics of each community,and the layout time is the shortest.