5G alarm processing system mirroring distributed cloud implementation method and device

Abstract

The invention discloses a 5G alarm processing system mirroring distributed cloud implementation method and device, and the method comprises the steps: carrying out the slicing of all alarm processing flows, and forming a plurality of alarm processing slice containers; grouping different alarms, wherein the alarms in each group are processed by an alarm processing slice container; each alarm processing slice container uses a cache database and is distributed with a database index number; and distributing the interaction task of the front-end system to the corresponding alarm processing slice container for processing through the management slice container. According to the method and the device, all alarm processing flows are sliced, namely alarm acquisition, alarm preprocessing and alarm processing are put together to form an alarm processing slice container, each alarm processing slice container is responsible for part of alarms, the processing of each alarm processing slice container is separated from each other and does not influence each other, and the alarm processing efficiency is improved. And finally storing the data in the same alarm library.

Description

technical field [0001] The invention relates to the field of computer communication core networks, in particular to a method and device for realizing mirroring and distributed cloud access of a 5G alarm processing system. Background technique [0002] In the 2G / 3G / 4G era, each functional layer of the alarm processing system of the core network is mainly distributed and run on each host, such as figure 1 As shown, messages are passed between functions through some queue middleware. [0003] (1) The first is the alarm collection layer, which is mainly for collection, analysis and data preprocessing of different alarm interfaces; [0004] (2) Then there is the alarm processing layer, which is rich in content, including functions such as alarm standardization, alarm compression, alarm clearing, and alarm association; [0005] (3) Queue middleware is generally used for message transmission between the alarm collection layer and the alarm processing layer, such as MQ (Message Qu...

AI Technical Summary

Problems solved by technology

[0008] (1) Poor performance scalability. In order to improve performance, in general, in addition to adding machine resources, programs and configurations need to be modified to achieve it;

[0009] (2) The coupling between various functions is high. Usually, an error in a process in the middle will affect the overall system. For example, an alarm storm suddenly breaks out on a certain alarm interface. In addition to the backlog of the queue, it is likely to cause some alarm processing The performance of functions is abnormally low, such as alarm correlation and alarm standardization, etc.; and these functions are generally integrated functions, so it will inevitably lead to slower processing of the entire system, and then lead to an increasingly serious backlog of all types of alarms;

[0010] (3) Some queue middleware failures or machine failures will affect many functions. Before going to the cloud, the general system programs are directly deployed on the physical machine, and the physical machine generally has sufficient memory, CPU, and disk. Many programs, once the machine fails, it will affect many processing processes, resulting in serious loss of alarms

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