云计算中网络通信服务目标数据高效检测仿真
胡东明;刘旭敏;徐维祥
【期刊名称】《计算机仿真》 【年(卷),期】2018(035)002
【摘要】An efficient detection method of target data based on compressive sensing reconstruction algorithm and support vector machine algorithm is proposed.Firstly,the compressive sensing technology is used to process the communication service data of detection nodes in lower level and construct the sparse matrix and the measurement matrix of communication service data,thus the accurate reconstruction of sparse unknown signal is completed.Secondly,the least squares method is used to obtain the amplitude information of nonzero
elements
in
network
data.Moreover,the
feature
of
reconstructed data is selected to calculate degree of approximation among features of communication service data.Finally,support vector machine is used to determine whether the communication service data is abnormal or not.Simulation results show that the proposed method can locate the linear boundary of communication service data accurately,which has high detection accuracy and recall level The false positive rate is low.%对通信服务目标数据的检测,能够有效提高网络通信服务质量.对目标数据的高效检测,需要获得网络数据非零元素的幅度信息,对重构后的数据进行特征选取,完成目标数据的检测.传统方法对网络测量数据时空特性进
云计算中网络通信服务目标数据高效检测仿真
