标题:Anomaly detection for cellular networks using big data analytics
作者:Li, Bing; Zhao, Shengjie; Zhang, Rongqing; Shi, Qingjiang; Yang, Kai
作者机构:[Li, Bing; Zhao, Shengjie; Yang, Kai] Tongji Univ, Key Lab Embedded Syst & Serv Comp, Minist Educ, Shanghai 201804, Peoples R China.; [Zhao, Shengji 更多
通讯作者:Zhao, Shengjie;Zhao, SJ;Zhao, SJ
通讯作者地址:[Zhao, SJ]Tongji Univ, Key Lab Embedded Syst & Serv Comp, Minist Educ, Shanghai 201804, Peoples R China;[Zhao, SJ]Tongji Univ, Sch Software Engn, Shan 更多
来源:IET COMMUNICATIONS
出版年:2019
卷:13
期:20
页码:3351-3359
DOI:10.1049/iet-com.2019.0765
关键词:Big Data; mobile computing; data analysis; Internet; cellular radio;; cellular networks; big data analytics; mobile technology; cellular; network big data; big data analytic-based anomaly detection method;; state-of-the-art techniques; mobile Internet; smart devices
摘要:Broadband connectivity and mobile technology have been widely applied in the world. With these advanced technologies, the proliferation of smart devices and their applications by accessing mobile internet have come up with a giant leap forward, leading to the ever-increasing scale and complexity of cellular networks. This presents imminent challenges to anomaly detection in cellular networks. In this study, the authors discuss challenges and current literature of anomaly detection for cellular networks to embrace the 'big data' era. First, they review the state-of-the-art techniques in the area of anomaly detection in cellular networks. Then, the challenges are pinpointed for anomaly detection due to the cellular network big data. Finally, they introduce a big data analytic-based anomaly detection method for cellular networks.
收录类别:EI;SCOPUS;SCIE
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077457978&doi=10.1049%2fiet-com.2019.0765&partnerID=40&md5=8dfdc22f12302dc3ce46c88751339ae4
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