摘要
针对传统网络负载异常监测方法中精准度较差、有效性较低等问题,本文提出一种基于爬虫大数据的网络负载异常监测方法。为了验证该方法的有效性,将其与传统监测方法进行对比实验。实验结果表明,该方法实用性和精准度更高,更适用于对网络负载异常的监测。
Aiming at the problems of poor accuracy and low effectiveness in traditional network load anomaly monitoring methods,this paper proposed a network load anomaly monitoring method based on crawler big data.In order to verify the effectiveness of this method,it was compared with the traditional monitoring method.Experimental results show that this method is more practical and accurate,and more suitable for monitoring network load anomalies.
作者
杨毅
YANG Yi(School of Information Engineering,Henan University of Animal Husbandry and Economy,Zhengzhou Henan 450018)
出处
《河南科技》
2019年第34期33-35,共3页
Henan Science and Technology
基金
河南省科技攻关项目(No.172102310554,No.192120110111)
河南牧业经济学院科研创新基金(No.XKYCXJJ2017008)
关键词
爬虫大数据
网络负载
异常监测
crawler big data
network load
abnormal monitoring