Device and method based on network big data storing, collecting and analyzing

Abstract

A device based on network big data storing, collecting and analyzing is disclosed. The device includes a host computer of the device and an installed operating system installed in the host computer, awireless network AP big data collection management software, a wireless network AP fault prediction and diagnosis software, a wireless network AP resource recovery and release software, a wireless network AP user location service software and a wireless network security management software. Also disclosed are a collection and storage method based on the device, a wireless network intelligent operation and maintenance method, a wireless network AP resource recovery and release method and a wireless network security judgment method. The invention has the advantages of strong self-determinationperformance, high stability, extremely high adaptability, safety and expansibility, can meet the needs of schools, government agencies, shopping malls, tourist attractions, improves the utilization oforiginal resources, and improves the level of smart city construction.

Description

technical field [0001] The invention relates to the technical field of network big data, in particular to a device and method for storing, collecting and analyzing network-based big data. Background technique [0002] With the increasing frequency of users using wireless WiFi, the number of APs deployed in local areas such as schools, government agencies, shopping malls, and tourist attractions is increasing, and the amount of data obtained by using APs is increasing. It is a school, a shopping mall, and a tourist attraction with a large flow of people. A single AP can obtain hundreds of reported data per minute. In general, the number of APs installed in a school, government agency, shopping mall, or tourist attraction can reach hundreds or even thousands. The amount of data that these APs can obtain every minute, every hour, and every day is huge, followed by the aggravation of maintenance tasks and the improvement of protection levels. Relying on purely manual methods ca...

AI Technical Summary

Problems solved by technology

The amount of data that these APs can obtain every minute, every hour, and every day is huge, followed by the aggravation of maintenance tasks and the improvement of protection levels. Schools, government agencies, shopping malls, tourist attractions, and enterprise-level wireless networks The "AC+AP" mode is generally used in the construction of the enterprise. In order to ensure the normal operation of the enterprise wireless network, it is necessary to ensure that the AC and AP operate stably and efficiently around the clock. If only manual monitoring is performed, the workload is unimaginable.

Wireless network maintenance personnel are often busy monitoring and handling a large number of routine alarms, and their skills are limited, so they are often unable to analyze various wireless hidden dangers in a timely manner, and cannot eliminate problems in the bud

Because the wireless network is too large, wireless network security risks cannot be discovered in time, resulting in the paralysis of the wireless network, a large number of human factors and human bottlenecks lead to a long failure time of the wireless network, slow business recovery, and low overall service quality

The shortcoming of above-mentioned prior art is: (1) because wireless AP quantity is huge staff can't carry out unified management to wireless network AP resources (that is the recovery and release of wireless network AP resources)

(2) Due to the huge number of wireless APs, manpower and material resources are invested and maintenance costs are high

(3) Wireless AP failure cannot be predicted in advance

(4) Due to the huge number of wireless APs, it is cumbersome to find faulty nodes and waste a lot of manpower and material resources

(5) Unable to timely issue early warnings of potential safety hazards and security loopholes in the wireless network, which lead to paralysis of the wireless network

(6) Failure to continuously collect, store and analyze wireless network data leads to loss of wireless network data

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