网络数据流传输数据断点区域检测仿真

摘要

This article puts forward a detection method for breakpoint region of network data based on improved multi-constraint label.Firstly,the connected graph model of data node is built to give topological measurement of data node distribution and to extract feature quantity of distribution probability density,and then transmission probability density of data point in each region is compared,and feature similarity is provided,thus normal data area and data breakpoint area are distinguished in line with distance between regional feature and cluster center.Finally,multi-label method is introduced to detect and restrict data region,and to carry out breakpoint area detection of transmission data of network data flow.The simulation results show that the method in this article has high accuracy rate.It can improve transmission quality of data packet.%对网络数据流传输下的数据断点进行区域检测,能够有效提高网络数据传输效率.对网络数据断点进行区域检测,需要区分正常数据与数据断点区域,引入多标签对数据区域检测约束,完成数据断点区域检测.传统方法首先组建数据断点区域检测模型,提取数据断点区域特征,但忽略了引入多标签对数据区域检测的约束,导致检测精度低.提出改进多约束标签网络数据断点区域检测方法.先构建数据节点连通图模型,给出数据节点分布拓扑测度,提取分布概率密度特征量,比较各区域数据点传输概率密度,给出其特征相似度,根据各区域特征与聚类中心之间的距离区分正常数据与数据断点区域,引入多标签方法对数据区域检测约束,进行网络数据流传输数据断点区域检测.仿真证明,所提方法准确率高,提升了数据包传输质量.