Intelligent anomaly detection and root cause analysis in mobile networks
AssigneeVMware, Inc.
InventorsManu Sharma, Deepak Khurana, Sarabjot Singh, Adnan Raja, Srikanth Hariharan, Aditya Gudipati, Manu Bansal, Duyen Riggs, Rakesh Misra
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Abstract
A method for automated root cause analysis in mobile radio access networks, including: determining mobile radio access network data (e.g., RAN data); detecting an anomaly for a set of user sessions and/or cells from the RAN data; and classifying the detected anomalies using a set of root cause classifiers.
Claims20
A method comprising:
- receiving radio access network data generated by a set of base stations;
- determining a plurality of user sessions from the radio access network data;
- detecting an anomalous user session from the plurality of user sessions;
- detecting an anomalous cell associated with the anomalous user session based on the radio access network data;
- determining a root cause of the anomalous user session;
- determining additional anomalous user sessions associated with the root cause and additional cell identifiers associated with the additional anomalous user sessions;
- and
- displaying an alert that comprises:
- a severity score based on a percentage of user sessions impacted by the root cause;
- a number of user sessions impacted by the root cause;
- and
- an indication of the root cause.
A non-transitory, computer-readable medium comprising instructions that, when executed by a hardware-based processor, perform stages for anomaly detection, the stages comprising:
- receiving radio access network data generated by a set of base stations;
- determining a plurality of user sessions from the radio access network data;
- detecting an anomalous user session from the plurality of user sessions;
- detecting an anomalous cell associated with the anomalous user session based on the radio access network data;
- determining a root cause of the anomalous user session;
- determining additional anomalous user sessions associated with the root cause and additional cell identifiers associated with the additional anomalous user sessions;
- and
- displaying an alert that comprises:
- a severity score based on a percentage of user sessions impacted by the root cause;
- a number of user sessions impacted by the root cause;
- and
- an indication of the root cause.
A system for anomaly detection, the system comprising:
- a hardware-based processor;
- and
- a non-transitory, computer-readable medium comprising instructions that, when executed by the processor, perform stages comprising:
- receiving radio access network data generated by a set of base stations;
- determining a plurality of user sessions from the radio access network data;
- detecting an anomalous user session from the plurality of user sessions;
- detecting an anomalous cell associated with the anomalous user session based on the radio access network data;
- determining a root cause of the anomalous user session;
- determining additional anomalous user sessions associated with the root cause and additional cell identifiers associated with the additional anomalous user sessions;
- and
- displaying an alert that comprises:
- a severity score based on a percentage of user sessions impacted by the root cause;
- a number of user sessions impacted by the root cause;
- and
- an indication of the root cause.
Dependencies are inferred from the claim text.