Anomaly detection and analysis framework for mobile networks
Jessica Mendoza, Isabel de-la-Bandera, Jesús Burgueño, Cesar Morillas, David Palacios, Raquel Barco · 2021
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.