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1. 发明申请

WO2017172541A1 SYSTEMS AND METHODS FOR MEASURING EFFECTIVE CUSTOMER IMPACT OF NETWORK PROBLEMS IN REAL-TIME USING STREAMING ANALYTICS 审中-公开
标题翻译：用于测量实时使用流式分析中的网络问题的有效客户影响的系统和方法
公开(公告)号：WO2017172541A1
公开(公告)日：2017-10-05
申请号：PCT/US2017/024158
申请日：2017-03-24
申请人： ANRITSU COMPANY
发明人： MEDAS, Carlo , MOTTA, Davide
IPC分类号： G06F11/34 , H04W24/02 , H04W24/08 , G06Q30/02
摘要： A system used for identifying issues within a telecom network. Data is obtained from sources including probes and network elements. KPIs are identified for real-time streaming aggregation. Streaming data related to the KPIs is aggregated and an approximation of count-distinct subscribers and volume count is calculated, as well as count-distinct subscribers aggregating by each identified KPI. Drill objects found in the aggregated data are identified based on the calculations and real-time trending records are generated and stored for each drill object using an exponential moving average. Baseline averages are generated based on the real-time trending records. An increase in errors can then be detected based on the baseline averages and additionally aggregated real-time streaming data. Deviations in each drill object contributing to the detected increase in errors are then analyzed and a full case report is generated based on details of the deviations.
摘要翻译：
用于识别电信网络内问题的系统。数据来源包括探针和网络元素。 KPI被识别用于实时流聚合。汇总与KPI相关的流数据并计算不同计数的订户和数量的近似值，以及按每个标识的KPI汇总的计数不同的订户。在汇总数据中找到的钻探对象基于计算进行识别，并使用指数移动平均值为每个钻探对象生成并存储实时趋势记录。基线平均值是基于实时趋势记录生成的。然后可以基于基线平均值和另外汇总的实时流数据来检测错误的增加。然后分析导致检测到的错误增加的每个钻探对象中的偏差，并基于偏差的细节生成完整的病例报告。

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