Network element anomaly detection method and device

Abstract

The embodiment of the invention provides a network element anomaly detection method and a network element anomaly detection device. The method comprises the following steps: modeling according to historical network data of a network element to obtain a network element behavior model; determining a space detection threshold and a time detection threshold; determining a current space quantization error and a current time quantization error; according to the current space quantization error and the space detection threshold, determining whether a current behavior has space anomaly or not; and according to the current time quantization error and the time detection threshold, determining whether the current behavior has time anomaly or not. According to the network element anomaly detection method and device provided by the embodiment of the invention, modeling is performed by the historical network data of the network element to obtain a network element behavior model, and time-space anomaly detection is carried out on the current behavior of the network element through utilizing a plurality of nerve cells and a context vector of the network element behavior model; compared with manual analysis of a network element anomaly performance index, the anomaly detection on a network element space and a time dimension can be realized and a network element troubleshooting capability is improved; and meanwhile, online anomaly detection can be realized and the automation level of network element troubleshooting is improved.

Description

technical field [0001] Embodiments of the present invention relate to the field of communication technologies, and in particular, to a method and device for detecting abnormalities of network elements. Background technique [0002] With the development of communication technology, mobile networks are becoming more and more complex, and the difficulty of network management and optimization is increasing. [0003] A mobile network includes a large number of network elements, some network elements need to interact with user terminals, and some network elements do not need to interact with user terminals. Usually network elements will generate a large amount of network data. Existing network element troubleshooting is mainly done by manually analyzing the abnormal performance indicators of network elements. The most common method is to preset the normal range of each network element performance indicator, and approximately judge the network element by judging whether the perfor...

AI Technical Summary

Problems solved by technology

[0004] In the existing technology, manual analysis of network element abnormal performance indicators not only results in insufficient network element troubleshooting capabilities, but also results in low network element troubleshooting efficiency

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