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Big data analysis and association based dynamic inspection-on-demand method

A data analysis and big data technology, applied in the field of big data analysis, can solve the problems of affecting the inspection effect, curing the inspection cycle, and unable to allocate inspection resources reasonably and effectively, so as to improve the inspection effect and improve the cost efficiency. Effect

Inactive Publication Date: 2016-12-21
INSPUR QILU SOFTWARE IND
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  • Summary
  • Abstract
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  • Claims
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Problems solved by technology

[0003] Usually, the base station adopts the static inspection mode, but there are many disadvantages in the static inspection mode, such as the fixed inspection period, the disconnection between the inspection and the network quality, the lack of pertinence in the task content, and the inability to verify the inspection effect. As a result, it is impossible to allocate inspection resources reasonably and effectively, and it is impossible to break through the barriers between inspection and troubleshooting, which seriously affects the inspection effect

Method used

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Embodiment

[0015] The dynamic on-demand inspection method based on big data analysis and association described in this embodiment establishes on-demand dynamic inspection and dynamic scheduling through big data analysis of operation and maintenance, and effectively allocates inspection resources by optimizing the inspection cycle and management mode , improve the inspection effect, and break the barriers between inspection and troubleshooting, and improve cost efficiency; it mainly includes the following steps: 1) Establish an analysis model, 2) Generate dynamic inspection tasks, 3) Execute inspection tasks and 4) Query the inspection result.

[0016] Step 1) Establishing an analysis model mainly refers to: starting from the needs of actual inspection work, combined with relatively static attributes such as the importance level and coverage area of ​​the base station itself, a total of 9 evaluation points from the three dimensions of external factors, network characteristics, and equipmen...

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Abstract

The invention discloses a dynamic on-demand inspection method based on big data analysis and association, which relates to the technical field of big data analysis. Through big data analysis of operation and maintenance, on-demand dynamic inspection and dynamic scheduling are established, and by optimizing the inspection period and management Mode, effectively allocate inspection resources, and at the same time, break down the barriers between inspection and fault handling; it mainly includes the following steps: 1) Establish an analysis model, 2) Generate dynamic inspection tasks, 3) Execute inspection tasks and 4) Query Inspection results. By adopting the invention, the inspection effect of the base station can be improved, and the barriers between the inspection fault processing can be broken, the cost efficiency can be improved, and the operation and maintenance management cost can be reduced.

Description

technical field [0001] The invention relates to the technical field of big data analysis, in particular to a dynamic on-demand inspection method based on big data analysis and correlation. Background technique [0002] Big data refers to a collection of data that cannot be captured, managed, and processed by conventional software tools within a certain period of time. It requires a new processing model to have stronger decision-making power, insight and discovery, and process optimization capabilities to adapt to massive and high growth rates. and diverse information assets. The strategic significance of big data technology lies in the professional processing of these meaningful data, improving the "processing ability" of data, and realizing the "value-added" of data through "processing". From a technical point of view, the relationship between big data and cloud computing is inseparable. Big data cannot be processed by a single computer, and must be processed using a dist...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G07C1/20
CPCG06Q10/0631G07C1/20
Inventor 陆清刘立力马立芳王东新
Owner INSPUR QILU SOFTWARE IND
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