基于DPI的LTE网络用户行为感知系统的设计与实现
发布时间：2018-10-20 14:32
【摘要】：针对电信运营商越发迫切的智能管道需求,提出了一种具有自学习功能的移动互联网用户行为感知系统的解决方案。本方案针对传统监测系统用户感知度低、统计能力不足等缺点,对现行LTE网络S1接口用户面协议进行分析,并结合当前互联网主流的行为分析技术——深度分组检测(DPI)技术和聚类爬虫技术的优势,实现了以协议解码、业务呼叫/事务详细记录(xDR)合成为基础的LTE网络用户行为精准分析。本系统经现网数据验证,能达到既定目标,对满足智能管道的需求具有一定的指导价值。
[Abstract]:Aiming at the increasingly urgent demand of intelligent pipeline for telecom operators, a solution of mobile Internet user behavior awareness system with self-learning function is proposed. Aiming at the shortcomings of the traditional monitoring system, such as low user perception and insufficient statistical ability, the current LTE network S1 interface user surface protocol is analyzed. Combined with the advantages of (DPI) technology and clustering crawler technology, the protocol decoding is realized. Accurate Analysis of the behavior of LTE Network users based on (xDR) composition of Service call / transaction details. The system is verified by the current network data, which can achieve the established goal, and has certain guiding value to meet the demand of intelligent pipeline.
【作者单位】： 重庆邮电大学通信网与测试技术重点实验室;
【基金】：国家高技术研究发展计划(“863”计划)基金资助项目(No.2014AA01A706) 2013年重庆高校创新团队基金资助项目
【分类号】：TN929.5
[Abstract]:Aiming at the increasingly urgent demand of intelligent pipeline for telecom operators, a solution of mobile Internet user behavior awareness system with self-learning function is proposed. Aiming at the shortcomings of the traditional monitoring system, such as low user perception and insufficient statistical ability, the current LTE network S1 interface user surface protocol is analyzed. Combined with the advantages of (DPI) technology and clustering crawler technology, the protocol decoding is realized. Accurate Analysis of the behavior of LTE Network users based on (xDR) composition of Service call / transaction details. The system is verified by the current network data, which can achieve the established goal, and has certain guiding value to meet the demand of intelligent pipeline.
【作者单位】： 重庆邮电大学通信网与测试技术重点实验室;
【基金】：国家高技术研究发展计划(“863”计划)基金资助项目(No.2014AA01A706) 2013年重庆高校创新团队基金资助项目
【分类号】：TN929.5
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