摘要
在线数据融合方法在网络流量检测中一直有融合精确度低、接收点差的问题。提出一种新的网络流量监测中在线数据融合方法,采集网络流量监测中的实时在线数据,通过卡尔曼滤波法对在线数据进行预测,获取网络流量状态值;并以此为基础,通过时空综合分析,计算节点的量测实时方差;并依据最小二乘准则,对数据进行加权处理,求出加权系数,引入加权数据融合算法,实现在线数据的融合。实验结果表明,改进的融合方法不仅融合精度高,而且所需能耗低,适应能力较强。
Online data fusion method in the network traffic detection has been low convergence accuracy,receiver is poor. Put forward a new kind of network traffic monitoring online data fusion method,the real-time online data collection network traffic monitoring,through the Kalman filtering method to forecast the online data,access to the network traffic state values,and based on this,through comprehensive analysis of time and space,real-time measurement variance of computing nodes,and based on the least squares criterion,the weighted data processing,and the weighted coefficient,introducing the weighted data fusion algorithm,realize the online data fusion. The experimental results show that the improved fusion method is not only the fusion accuracy is high,and low energy consumption,strong ability to adapt.
出处
《科学技术与工程》
北大核心
2016年第13期239-243,共5页
Science Technology and Engineering
基金
江苏省现代教育技术研究课题(2015-R-4585)资助
关键词
网络流量
在线数据
融合方法
network traffic
online data
fusion method
