Fault detection method for centralized access network

An access network and centralized technology, applied in the direction of data exchange network, digital transmission system, electrical components, etc., can solve problems such as difficulty in obtaining fault samples at one time, unsuitable for centralized access network, etc., to improve fault detection efficiency , Reduce the amount of manual participation and improve the effect of automation

Pending Publication Date: 2019-09-10
北京中科晶上科技股份有限公司
View PDF5 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, for most devices, it is difficult to obtain a large number of fault sam

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Fault detection method for centralized access network
  • Fault detection method for centralized access network
  • Fault detection method for centralized access network

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0051]

[0052] The method of training the first fault detector will be introduced below through an embodiment.

[0053] For most centralized access networks, the network architecture can be abstracted into multiple layers. Since each layer has different characteristics, according to an embodiment of the present invention, the network architecture of the centralized access network can be targeted at each layer. The first fault detectors are trained separately to use the first fault detector corresponding to the layer to detect abnormal events when performing abnormal detection.

[0054] For the above embodiment, when training the first fault detector, the corresponding operating data of the layer can be selected in combination with the characteristics of each layer to be used as the training sample of the negative selection algorithm, and the same category as the training sample can be selected when step 1 is implemented. Anomaly detection is performed on the data to be tested.

[0...

Example Embodiment

[0105]

[0106] According to Embodiment 2 of the present invention, a method for performing anomaly detection on a centralized access network is provided, refer to figure 2 , The method includes:

[0107] Step 1. For the centralized access network, a first fault detector is used for abnormal event detection, wherein the first fault detector is obtained by training using a negative selection algorithm based on the operating data of the centralized access network itself.

[0108] According to an embodiment of the present invention, the method in Embodiment 1 is used to train to obtain the first fault detector.

[0109] The inventor found that the characteristics of the failure of the above-mentioned layers conform to the following law, that is, if the current layer fails, the lower layer has a great probability of abnormality. For example, if the indicators of the network layer are abnormal, the lower network element layer usually also has abnormalities. Therefore, it is often imposs...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

A method for executing anomaly detection on a centralized access network comprises the steps that (1) for one layer in a network architecture of the centralized access network, a first fault detectorcorresponding to the layer is adopted for abnormal event detection, and the first fault detector is obtained through training by adopting a negative selection algorithm based on operation data of thelayer; (2) when the first fault detector detects that one component has multiple pieces of fault information, the first fault detector detects that the component has multiple pieces of fault information; a second fault detector is employed to perform an intersection operation on a plurality of pieces of fault information of the component to determine a fault of the component, wherein one of the pieces of fault information is represented as a set of abnormal events occurring on the component and all abnormal events associated with the abnormal event.

Description

technical field [0001] The invention relates to fault detection of a wireless communication system, in particular to fault detection for a centralized access network. Background technique [0002] Centralized access network (C-RAN) is a new type of resource management and control system, which creates a large number of virtual base stations on demand in a large-scale centralized resource pool through a unified and open interface, so as to realize sharing between multiple virtual base stations resource. However, for such a shared resource pool, once there is a problem with the resources in the resource pool, it may cause failures of multiple base stations associated with it, which will affect the services of access users in a wide range, and even cause the entire network to fail. collapse. Therefore, it is necessary to set up a fault management system for the centralized access network. [0003] Fault detection is the first step of fault management, and its detection effec...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): H04W24/04H04L12/24
CPCH04W24/04H04L41/065H04L41/0631
Inventor 叶冠文王园园张宗帅孙茜
Owner 北京中科晶上科技股份有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products