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Anomaly detection and analysis framework for mobile networks

机译:移动网络的异常检测和分析框架

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Proper management of failures in mobile communication networks is essential to provide quality services to users. This management consists of several tasks, being the first of them the detection of network failures. To carry out this task, key performance indicators (KPIs) that reflect the network state are analyzed. However, due to the different nature of these KPIs, the same detection method is not able to correctly find the anomalies in all of them. In addition, most of the techniques proposed at the moment, focus on the detection of certain types of anomalies. This paper proposes a framework for the detection of anomalies, capable of finding different types of anomalies in KPIs of different nature. This framework includes as well certain configuration parameters that allow to perform the detection based on the policies of network operators. As a result, the proposed framework indicates which of the anomalies found are actually KPI degradations as well as the start and end time of each degradation, and its percentage of degradation with respect to the normal behavior of the KPI.
机译:适当管理移动通信网络中的失败对于向用户提供优质服务至关重要。此管理由多项任务组成,是首先检测网络故障。要执行此任务,分析反映网络状态的关键绩效指标(KPI)。然而,由于这些KPI的不同性质,相同的检测方法无法正确地找到所有这些中的异常。此外,目前提出的大部分技术,重点是检测某些类型的异常。本文提出了一种用于检测异常的框架,能够在不同性质的KPI中寻找不同类型的异常。该框架还包括某些配置参数,允许基于网络运营商的策略执行检测。结果,所提出的框架表明,发现的哪个异常实际上是KPI降级以及每次降级的开始和结束时间,以及相对于KPI的正常行为的劣化百分比。

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