Mobile internet operation data intelligent management system based on big data

Abstract

The invention discloses a mobile internet operation data intelligent management system based on big data, and relates to the field of data management, and the system comprises an operation intelligent management center which is provided with a data collection module, an operation monitoring module, a big data analysis module, an operation coordination module and an intelligent management module; the data acquisition module is used for acquiring internet base station data, network equipment data, equipment state data and user behavior data; the operation monitoring module is used for setting a generalized monitoring image and carrying out classification processing on the generalized monitoring image to generate a monitoring visual image; the big data analysis module obtains a corresponding operation coordination data packet according to the monitoring visual image; the operation coordination module is used for generating a personalized operation image according to the user behavior data, and comparing and analyzing the personalized operation image with the operation coordination data packet to obtain a dynamic resource optimization configuration result; the intelligent management module is used for performing coordination management according to the optimization result; according to the invention, the resource utilization rate in the data operation process is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data management, and in particular to an intelligent management system for mobile Internet operation data based on big data. Background Art

[0002] With the rapid development of information technology, the mobile Internet has penetrated into all aspects of social life, and its application scenarios have become increasingly rich, covering many fields such as social entertainment, e-commerce, online education, and mobile office, and have become an indispensable part of people's daily life and work; however, with the expansion of the application scope and the increase in the usage amount of the mobile Internet, the mobile Internet needs to meet various functional requirements such as strong data real-time performance, strong data analysis ability, and data security; therefore, it is an urgent problem for us to intelligently manage the operation data of the mobile Internet, realize the smooth operation of the corresponding mobile Internet, and avoid resource waste to the greatest extent. For this reason, the present invention proposes an intelligent management system for mobile Internet operation data based on big data. Summary of the Invention

[0003] The purpose of the present invention is to solve the defect of resource waste in the prior art, and to propose an intelligent management system for mobile Internet operation data based on big data.

[0004] In order to achieve the above purpose, the present invention adopts the following technical solutions:

[0005] An intelligent management system for mobile Internet operation data based on big data, including an operation intelligent management center, and the operation intelligent management center includes a data acquisition module, an operation monitoring module, a big data analysis module, an operation coordination module, and an intelligent management module;

[0006] The data acquisition module is used to collect Internet base station data, network device data, device status data, and user behavior data corresponding to the corresponding management area;

[0007] The operation monitoring module is used to analyze and process the obtained Internet base station data and network device data, obtain a generalized monitoring image, and perform operation monitoring classification processing on the corresponding device status data according to the generalized monitoring image to generate a corresponding monitoring visualization image;

[0008] The big data analysis module is used to perform matching analysis according to the operation monitoring classification processing results in the corresponding monitoring visualization image, obtain the coordination matching index corresponding to different management areas, and generate a corresponding operation coordination data packet;

[0009] The operation coordination module is used to generate personalized operation images corresponding to the corresponding monitoring areas according to the device status data and user behavior data, compare and analyze the obtained personalized operation images with the corresponding operation coordination data packets, and perform dynamic resource optimization configuration processing according to the comparison and analysis results;

[0010] The intelligent management module is used to intelligently allocate and manage the mobile Internet resources within the corresponding monitoring areas according to the dynamic resource optimization configuration results.

[0011] The above technical solution further includes: The process of collecting Internet base station data, network device data, device status data, and user behavior data corresponding to the management area includes:

[0012] Obtain the management area range of the operation intelligent management center, obtain the corresponding base station collection permissions according to the management area range, and collect the Internet base station data of the corresponding base station devices within the corresponding management area range. The Internet base station data is the base station configuration data and operation status data corresponding to the corresponding base station;

[0013] Set a base station hardware monitoring terminal in the corresponding base station device, and obtain the connected network device data and device status data through the base station hardware monitoring terminal;

[0014] Set corresponding signaling and traffic probes according to the network device data, and obtain the user behavior data corresponding to the corresponding mobile Internet devices according to the signaling and traffic probes;

[0015] Mark the collected data according to the corresponding time information and location information.

[0016] Further, the process of obtaining the generalized surveillance image includes:

[0017] Obtain the location information corresponding to each base station device, set the corresponding management center points according to the location information of the corresponding base station devices, obtain the location information corresponding to the corresponding network device data, and generate an initial device image according to the location information of each data;

[0018] Obtain the area monitoring radius R and area monitoring period T of the corresponding management center point setting area in the initial device image, and obtain the network device area data WY of the network device areas connected to the corresponding base station devices in the initial device image according to the area monitoring radius rt , through the formula WY rt = Calculate to obtain the network device area data WY rt , perform a finite-term summation on the network device area data WY rt to obtain the network device comprehensive data WZ T , and the obtained network device area data WYrt and the comprehensive data WZ of the network device T respectively conduct correlation analysis with the Internet base station data HJ;

[0019] Set corresponding area monitoring indicators and comprehensive monitoring indicators according to the corresponding correlation data;

[0020] Evaluate and analyze the obtained network device data according to the area monitoring indicators and comprehensive monitoring indicators respectively, obtain the corresponding evaluation deviation data, perform pixel value mapping processing on the obtained evaluation deviation data, and map it to the corresponding initial device image according to the pixel value mapping processing result to obtain the corresponding generalized monitoring image.

[0021] Further, the process of generating the monitoring visualization image includes:

[0022] Pre-store the corresponding classification evaluation system in the corresponding generalized monitoring image. The classification evaluation system includes classification evaluation indicators corresponding to the status of a single device and classification evaluation indicators corresponding to the overall device status in the area;

[0023] Set a single evaluation index set and an area evaluation index set according to the classification evaluation system;

[0024] Traverse and match the device status data corresponding to the corresponding network device data in the generalized monitoring image with the single evaluation index set to obtain the corresponding classification results. Quantitatively count the classification results corresponding to the device status data in the ring management area, and traverse and match the quantitative statistical results with the area evaluation index set to obtain the classification results of the corresponding ring management area;

[0025] Perform identification processing according to the corresponding classification results, and generate a monitoring visualization image according to the identification results.

[0026] Further, the process of generating the corresponding operation coordination data packet includes:

[0027] Sort the classification results corresponding to the area evaluation index set and the single evaluation index set according to the corresponding time sequence, perform filling processing based on the linear interpolation formula according to the sorting processing result of the time sequence, set corresponding time series data and signal conversion data for the filled classification results, and obtain corresponding periodic characteristic data according to the corresponding time series data and signal conversion data;

[0028] Statistically analyze the obtained periodic characteristic data, obtain q characteristic values corresponding to each unit time, generate a characteristic standard value set, and analyze the characteristic standard value set to obtain the characteristic evaluation indicators corresponding to the corresponding periodic characteristic data;

[0029] The obtained monitoring areas are combined and analyzed to generate corresponding control groups. The corresponding periodic feature data and feature evaluation indicators within the control groups are analyzed for comparison to obtain the deviation data corresponding to the feature evaluation indicators within the corresponding unit time. Corresponding coordination and matching data are obtained based on the corresponding deviation data. The coordination and matching data of each control group corresponding to the corresponding monitoring areas are compared and analyzed, sorted according to the comparison and analysis results to obtain the coordination and matching index of the corresponding control group, and an operation coordination data packet is generated according to the corresponding coordination and matching index.

[0030] Further, the process of generating the personalized operation image corresponding to the corresponding monitoring area includes:

[0031] Obtain the device status data and user behavior data corresponding to the corresponding network device data, analyze and process the user behavior data to obtain the corresponding user behavior data set, and analyze and train the user behavior data set based on the deep learning algorithm to construct the corresponding personalized user behavior model;

[0032] Input the user behavior data into the personalized user behavior model, output the corresponding deviation data, and construct the corresponding personalized operation image through visual display according to the corresponding time information and the deviation data corresponding to the corresponding feature evaluation indicators.

[0033] Further, the process of comparing and analyzing the obtained personalized operation image with the corresponding operation coordination data packet includes:

[0034] Complement and integrate the personalized operation image corresponding to the corresponding monitoring area according to the corresponding feature evaluation indicators, and obtain the corresponding operation coordination data according to the result of the regional complement and integration;

[0035] Perform weighted processing on the obtained operation coordination data and the corresponding coordination and matching index within the operation coordination data packet to obtain the priority coordination data of the corresponding monitoring area;

[0036] Sort and integrate the obtained priority coordination data, obtain the monitoring visualization image corresponding to the corresponding monitoring area according to the sorting and integration result, and set the resource allocation data according to the corresponding device status data and the corresponding Internet base station data within the monitoring visualization image;

[0037] Dynamically optimize the resource allocation of the resource allocation data corresponding to the corresponding monitoring area according to the corresponding priority coordination data for the operation coordination data, and obtain the corresponding result of the dynamic resource optimization configuration process, where the result of the dynamic resource optimization configuration process is obtained by matching according to the deviation data corresponding to the corresponding personalized operation image.

[0038] Further, the process of intelligently allocating and managing the mobile Internet resources within the corresponding monitoring area includes:

[0039] Feed the processing result of dynamic resource optimization configuration back to the intelligent management module corresponding to the corresponding base station device. Through the intelligent management module, allocate and manage the operation resource data of the corresponding base station device according to the processing result of dynamic resource optimization configuration, so that the corresponding mobile Internet devices in each monitoring area can operate normally.

[0040] The present invention has the following beneficial effects:

[0041] 1. In the present invention, by collecting Internet base station data, network device data, device status data, and user behavior data in the corresponding management area, analyzing and processing the Internet base station data, network device data, device status data, and user behavior data respectively according to the collection results, obtaining the corresponding generalized monitoring image, monitoring visualization image, and personalized operation image, refining the corresponding network devices in the management area through the generalized monitoring image to obtain the corresponding monitoring visualization image, dividing the monitoring area through the monitoring visualization image, setting the corresponding coordination matching index according to the monitoring area division result, and coordinating the data in the corresponding monitoring area according to the coordination matching index, thereby improving the coordinated utilization of resources between each monitoring area to a certain extent and improving the utilization rate of the corresponding resources in the monitoring area.

[0042] 2. In the present invention, by analyzing and processing the user behavior data in the monitoring area to obtain the corresponding personalized operation image, and judging the resource allocation data of the corresponding user from the personalized operation image, during the dynamic resource optimization configuration process, the resources are divided according to the user's usage behavior habits, thereby ensuring the improvement of the resource utilization rate to a certain extent and combining the user's usage habits to the greatest extent, thus improving the user's personalized needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a schematic structural diagram of an intelligent management system for mobile Internet operation data based on big data proposed by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0044] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0045] Embodiment 1

[0046] As Figure 1As shown in the figure, an intelligent management system for mobile Internet operation data based on big data proposed by the present invention includes an operation intelligent management center, and a data acquisition module, an operation monitoring module, a big data analysis module, an operation coordination module, and an intelligent management module are arranged in the operation intelligent management center.

[0047] In this embodiment, the operation intelligent management center is used to analyze and process the user behavior data corresponding to the mobile Internet devices in the corresponding area, monitor and manage the data operation process of the mobile Internet devices in the area according to the analysis results of the user behavior data, and coordinate and process the operation process of the corresponding mobile Internet devices according to the monitoring and processing results, so as to ensure that the data operation processes of the mobile Internet devices in the corresponding area can all run smoothly, and integrate the coordination process according to the user behavior data of the corresponding mobile Internet devices, so as to ensure the smoothness of the operation within the scope of the corresponding user requirements, thereby improving the rationality of data distribution and resource utilization rate. Its specific implementation process includes:

[0048] The data acquisition module is used to collect Internet base station data, network device data, device status data, and user behavior data corresponding to the corresponding management area;

[0049] The operation monitoring module is used to analyze and process the obtained Internet base station data and network device data, obtain a generalized monitoring image, and perform operation monitoring classification processing on the corresponding device status data according to the generalized monitoring image to generate a corresponding monitoring visualization image;

[0050] The big data analysis module is used to perform matching analysis according to the operation monitoring classification processing results in the corresponding monitoring visualization image, obtain the coordination matching index corresponding to different management areas, and generate a corresponding operation coordination data packet;

[0051] The operation coordination module is used to generate a personalized operation image corresponding to the corresponding monitoring area according to the device status data and the user behavior data, compare and analyze the obtained personalized operation image with the corresponding operation coordination data packet, and perform dynamic resource optimization configuration processing according to the comparison and analysis results;

[0052] The intelligent management module is used to perform intelligent allocation management on the mobile Internet resources in the corresponding monitoring area according to the dynamic resource optimization configuration results.

[0053] Embodiment 2

[0054] Based on Embodiment 1, in this embodiment, the specific implementation processes of the data acquisition module, the operation monitoring module, the big data analysis module, the operation coordination module, and the intelligent management module arranged in the operation intelligent management center are described in detail, where:

[0055] The data acquisition module is used to collect Internet base station data, network device data, device status data, and user behavior data within the corresponding area, and send the collected data information to the operation monitoring module. The specific implementation process includes:

[0056] Set up a management collection unit and a device collection unit;

[0057] Collect Internet base station data and network device data within the corresponding area through the management collection unit. The management collection unit obtains the management area range of the operation intelligent management center, obtains the base station collection permissions within the management area range, and collects the Internet base station data of the corresponding base station devices within the corresponding management area range according to the corresponding base station collection permissions. The Internet base station data is the base station configuration data and operation status data corresponding to the corresponding base station, where:

[0058] The base station configuration data includes base station identification information, geographical location information, hardware configuration information, etc.;

[0059] The operation status data includes base station device operation status data, signal quality data, and connection status data. The base station device operation status data includes the performance data of the corresponding base station device;

[0060] Set up a base station hardware monitoring terminal according to the corresponding Internet base station data within the management area range. The base station hardware monitoring terminal obtains the mobile Internet devices connected to the corresponding base station through the corresponding network management protocol, integrates the mobile Internet devices connected to the corresponding base station, and obtains the corresponding network device data;

[0061] Collect the corresponding device status data and user behavior data through the device collection unit. The specific implementation process includes:

[0062] Perform device status analysis on the network device data obtained by the base station hardware monitoring terminal, monitor and process the network device data based on the network layer corresponding to the corresponding base station hardware monitoring terminal, and obtain the device status data corresponding to the corresponding network device data. The device status data is the signal strength, signal quality, and connection stability data corresponding to the corresponding network device data within the base station corresponding to the corresponding management area range;

[0063] Obtain the signaling and traffic probes corresponding to the corresponding network device data within the base station corresponding to the corresponding management area range, monitor the user behavior data corresponding to the corresponding network device data according to the signaling and traffic probes corresponding to the corresponding network device data, and obtain the user behavior data corresponding to the corresponding network device data. The user behavior data includes the signaling data and traffic data of the corresponding network device;

[0064] Mark the time information and location information for the Internet base station data, network device data, device status data, and user behavior data collected by the management collection unit and the device collection unit respectively, and send them to the operation monitoring module for monitoring and processing according to the time information and location information marking results.

[0065] The operation monitoring module is used to analyze and process the obtained Internet base station data and network device data, obtain a generalized surveillance image, and perform operation monitoring classification processing on the corresponding device status data according to the generalized surveillance image to generate a corresponding monitoring visualization image. The specific implementation process includes:

[0066] Set up a generalized monitoring unit and a classification processing unit;

[0067] Through the generalized monitoring unit, analyze and process the Internet base station data, network device data, and device status data obtained by each base station device within the corresponding management area, quantify the operation process of the corresponding base station device, and generate a corresponding generalized surveillance image according to the quantification result. The specific implementation process includes:

[0068] Mark the Internet base station data as HJ, and mark the network device data corresponding to the corresponding time information and location information as WS st , where s is the location information corresponding to the network device data, and t is the time information corresponding to the network device data;

[0069] Perform correlation analysis on the Internet base station data HJ and the network device data WS st According to the corresponding location information in the network device data WS st Map the corresponding network device data to the corresponding location within the management area, obtain the initial device image within the corresponding management area according to the mapping result, and analyze and process the network device data and the Internet base station data according to the initial device image. The specific implementation process includes:

[0070] Obtain the distribution of the corresponding network device data in the initial device image, set the corresponding regional monitoring radius R and regional monitoring period T in the initial device image according to the location information where the Internet base station data is located, and obtain the network device area data WY corresponding to each circular ring management area in the initial device image rt , where:

[0071] α is the weight factor of the initial device image corresponding to the corresponding regional monitoring radius. Perform a finite-term summation on the network device area data WY rt to obtain the network device comprehensive data WZ corresponding to the initial device image T , where: m is the quantity of the data of the corresponding network device area;

[0072] Perform correlation analysis on the obtained network device area data WY rt and the network device comprehensive data WZ T respectively with the Internet base station data HJ, perform data preprocessing on the obtained data information, obtain the corresponding standard data set, map the obtained standard data set into a two-dimensional space coordinate system, respectively obtain the correlation curves of the network device area data and the network device comprehensive data with respect to the Internet base station data, perform correlation analysis on the obtained correlation curves, and obtain the corresponding correlation data P(X, Y), where X and Y are the data types corresponding to the corresponding variables respectively, X = (x 1 , x 2 , …, x n ), Y = (y 1 , y 2 , …, y n ) respectively correspond to the coordinates of the two-dimensional space coordinate system corresponding to the correlation curve;

[0073] wherein, x i and y i respectively correspond to the corresponding two-dimensional curves;

[0074] Set the corresponding area monitoring index and comprehensive monitoring index according to the corresponding correlation data;

[0075] Evaluate and analyze the obtained network device data respectively according to the area monitoring index and the comprehensive monitoring index, obtain the corresponding evaluation deviation data, perform pixel value mapping processing on the obtained evaluation deviation data, map it into the corresponding initial device image according to the pixel value mapping processing result, obtain the corresponding generalized monitoring image, and send the generalized monitoring image to the classification processing unit;

[0076] The classification processing unit is used to perform classification processing according to the generalized monitoring image to obtain a monitoring visualization image, and its specific implementation process includes:

[0077] Perform priority sorting according to the pixel values corresponding to the corresponding mapping results in the generalized monitoring image, obtain the evaluation deviation data corresponding to the corresponding pixel values, set the priority data corresponding to the corresponding generalized monitoring image and the corresponding monitoring area therein according to the evaluation deviation data, and perform operation monitoring classification processing on the corresponding device status data and user behavior data in sequence;

[0078] wherein, a classification evaluation system corresponding to the device status data is pre-stored in the generalized monitoring image, and different classification evaluation systems include classification evaluation indicators corresponding to a single device and classification evaluation indicators corresponding to multiple devices in the area;

[0079] Set up a single evaluation index set and a regional evaluation index set according to the classification evaluation system respectively;

[0080] Traverse and match the corresponding equipment status data in the generalized monitoring image with the single evaluation index set corresponding to the corresponding classification evaluation index to obtain the classification results of the corresponding equipment status data and user behavior data;

[0081] Conduct quantitative statistics on the corresponding classification results, and traverse and match the obtained quantitative statistical results with the regional evaluation index set corresponding to the corresponding classification evaluation index to obtain the classification results of the equipment status data and user behavior data corresponding to the corresponding monitoring area;

[0082] Set corresponding horizontal and vertical table marks for the classification results corresponding to the regional evaluation index set and the single evaluation index set respectively, where the horizontal is the monitoring result within the corresponding area, and the vertical is the monitoring result of the corresponding single type of data;

[0083] Perform identification processing on the horizontal and vertical table mark results and the corresponding classification results, and generate a monitoring visualization image according to the identification results.

[0084] The big data analysis module is used to perform matching analysis according to the operation monitoring classification processing results in the corresponding monitoring visualization image, obtain the coordination matching index corresponding to different management areas, and generate corresponding operation coordination data packets. The specific implementation process includes:

[0085] Obtain the corresponding horizontal and vertical table mark results in the monitoring visualization image, analyze and process the horizontal and vertical table mark results, and obtain the operation monitoring period corresponding to each monitoring area, where:

[0086] Sort the horizontal and vertical table mark results set for the classification results corresponding to the regional evaluation index set and the single evaluation index set according to the corresponding time sequence;

[0087] Obtain the corresponding operation monitoring periods for the horizontal processing and vertical processing results in the horizontal and vertical table mark results respectively according to the sorting results in time sequence;

[0088] Perform missing value processing on the data corresponding to the horizontal processing result and the vertical processing result respectively, and fill it based on the linear interpolation formula;

[0089] Set corresponding time series data and signal conversion data for the horizontal processing result and the vertical processing result after the filling process, mark the time series data as t, and mark the signal conversion data corresponding to the corresponding time series data as f(t) to obtain the corresponding periodic feature data W f (a, b), where:

[0090] Among them, a is the corresponding scale parameter, and b is the corresponding translation parameter. The signal conversion data is controlled and converted by the scale parameter and the translation parameter. According to the control conversion result, the distribution and change of the signal conversion data under different scale parameters and translation parameters are obtained. According to the corresponding change situation, the periodic feature data corresponding to the corresponding horizontal processing result and vertical processing result is obtained;

[0091] According to the obtained periodic feature data, the corresponding feature standard value corresponding to the corresponding unit time is set, and the feature values within the period corresponding to the corresponding periodic feature data are statistically analyzed to obtain the corresponding feature standard value. p periodic feature data are obtained, q feature values corresponding to each unit time are obtained, a feature standard value set is generated, and the feature standard value set is analyzed and processed to obtain the corresponding standard deviation data S, where:

[0092] Among them, According to the corresponding standard deviation data, the feature evaluation index corresponding to the corresponding periodic feature data is obtained;

[0093] According to the periodic feature data and feature evaluation indexes of each monitoring area and a single mobile Internet device, analysis and processing are carried out to obtain the corresponding coordination matching index. The specific implementation process includes:

[0094] The obtained monitoring areas are combined and analyzed to obtain the corresponding control group. The corresponding periodic feature data and feature evaluation indexes within the control group are compared and analyzed to obtain the deviation data corresponding to the feature evaluation index within the corresponding unit time. The deviation data within the unit time is integrated and processed to obtain the corresponding weight reference coefficient of the unit time. According to the weight reference coefficient of the unit time and the deviation data, the coordination matching data of the corresponding control group is obtained;

[0095] The coordination matching data of each control group corresponding to the corresponding monitoring area are compared and analyzed, sorted according to the comparison analysis result, the coordination matching index of the corresponding control group is obtained according to the sorting result, a corresponding operation coordination data packet is generated according to each coordination matching index, and the corresponding operation coordination data packet is sent to the operation coordination module.

[0096] The operation coordination module is used to generate a personalized operation image corresponding to the corresponding monitoring area according to the device status data and user behavior data, compare and analyze the obtained personalized operation image with the corresponding operation coordination data packet, and perform dynamic resource optimization configuration processing according to the comparison analysis result. The specific implementation process includes:

[0097] Set a personalized analysis unit and a coordination analysis unit;

[0098] The personalized analysis unit is used to obtain the device status data and user behavior data corresponding to the corresponding network device data, analyze and process the user behavior data to obtain the corresponding user behavior data set, analyze and train the user behavior data set based on the deep learning algorithm, and construct the corresponding personalized user behavior model;

[0099] Input the user behavior data into the personalized user behavior model, output the corresponding deviation data, and perform visual display based on the deviation data corresponding to the corresponding time information and the corresponding feature evaluation index to construct the corresponding personalized operation image. The personalized operation image includes the deviation data corresponding to each user in the corresponding monitoring area. Visualize the idle deviation data and the load deviation data through the corresponding RGB values, so as to facilitate the coordination analysis unit to perform regional complementary integration on the personalized operation image in the corresponding monitoring area;

[0100] The coordination analysis unit is used to perform regional complementary integration on the personalized operation image corresponding to the corresponding monitoring area according to the corresponding feature evaluation index. The specific implementation process includes:

[0101] Integrate the personalized operation image corresponding to the corresponding monitoring area according to the corresponding RGB value to obtain the regional comprehensive idle data and the regional comprehensive load data;

[0102] Perform mapping difference analysis on the obtained regional comprehensive idle data and regional comprehensive load data according to the corresponding RGB values in the corresponding monitoring area, perform intra-regional complementary integration according to the deviation data corresponding to the RGB values of the personalized operation image corresponding to the corresponding user, analyze and process the intra-regional complementary integration results of each monitoring area corresponding to the intra-regional complementary integration results between regions to obtain the inter-regional complementary integration results, and obtain the corresponding operation coordination data according to the regional complementary integration results;

[0103] Perform weighted processing on the obtained operation coordination data and the corresponding coordination matching index in the operation coordination data packet to obtain the priority coordination data of the corresponding monitoring area;

[0104] Sort and integrate the obtained priority coordination data, obtain the monitoring visualization image corresponding to the corresponding monitoring area according to the sorting and integration results, and set the resource allocation data according to the corresponding device status data and the corresponding Internet base station data in the monitoring visualization image;

[0105] Perform dynamic resource optimization configuration processing on the resource allocation data corresponding to the corresponding monitoring area according to the corresponding priority coordination data of the operation coordination data to obtain the corresponding dynamic resource optimization configuration processing result, and the dynamic resource optimization configuration processing result is obtained by matching according to the deviation data corresponding to the corresponding personalized operation image.

[0106] The intelligent management module is used to intelligently allocate and manage the mobile Internet resources in the corresponding monitoring area according to the corresponding dynamic resource optimization configuration results. The specific implementation process includes:

[0107] Feed back the dynamic resource optimization configuration processing results to the intelligent management module corresponding to the corresponding base station device. Through the intelligent management module, allocate and manage the operation resource data of the corresponding base station device according to the dynamic resource optimization configuration processing results, so that the corresponding mobile Internet devices in each monitoring area operate normally.

[0108] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A mobile Internet operation data intelligent management system based on big data, including an operation intelligent management center, characterized in that: The operation intelligent management center includes a data acquisition module, an operation monitoring module, a big data analysis module, an operation coordination module and an intelligent management module; The data collection module is used to collect Internet base station data, network equipment data, equipment status data and user behavior data corresponding to the corresponding management area; The operation monitoring module is used to analyze and process the acquired Internet base station data and network equipment data, obtain a generalized monitoring image, perform operation monitoring classification processing on the corresponding equipment status data according to the generalized monitoring image, and generate a corresponding monitoring visualization image; The big data analysis module is used to perform matching analysis based on the operation monitoring classification processing results in the corresponding monitoring visualization image, obtain the coordination matching index corresponding to different management areas, and generate corresponding operation coordination data packets; The operation coordination module is used to generate a personalized operation image corresponding to the corresponding monitoring area according to the equipment status data and user behavior data, compare and analyze the obtained personalized operation image with the corresponding operation coordination data packet, and perform dynamic resource optimization configuration processing according to the comparison and analysis results; The intelligent management module is used to intelligently allocate and manage mobile Internet resources in the corresponding monitoring area based on the results of dynamic resource optimization configuration.

2. According to the big data-based intelligent management system for mobile Internet operation data according to claim 1, it is characterized in that: The process of collecting Internet base station data, network equipment data, equipment status data and user behavior data corresponding to the management area includes: Obtain the management area scope of the operation intelligent management center, obtain the corresponding base station collection authority according to the management area scope, and collect the Internet base station data of the corresponding base station equipment within the corresponding management area according to the base station collection authority, wherein the Internet base station data is the base station configuration data and operation status data corresponding to the corresponding base station; A base station hardware monitoring terminal is set in the corresponding base station equipment, and the connected network equipment data and equipment status data are obtained through the base station hardware monitoring terminal; Set corresponding signaling and traffic probes according to network device data, and obtain user behavior data corresponding to the corresponding mobile Internet devices according to the signaling and traffic probes; The collected data is marked according to the corresponding time information and location information.

3. According to the big data-based intelligent management system for mobile Internet operation data according to claim 2, it is characterized in that: The process of acquiring generalized surveillance images includes: Obtaining the location information corresponding to each base station device, setting the corresponding management center point according to the location information of the corresponding base station device, obtaining the location information corresponding to the corresponding network device data, and generating an initial device image according to the location information of each data; Get the corresponding management center point in the initial device image to set the regional monitoring radius R and regional monitoring period T, and obtain the network device area data WY connected to the corresponding base station equipment in each circular management area in the initial device image according to the regional monitoring radius rt , through the formula Calculate and obtain network equipment area data WY rt , for network device area data WY rt Perform finite item summation to obtain comprehensive network equipment data WZ T , the obtained network device area data WY rt And network equipment comprehensive data WZ T Conduct correlation analysis with Internet base station data HJ respectively; Set corresponding regional monitoring indicators and comprehensive monitoring indicators according to corresponding correlation data; The obtained network equipment data are evaluated and analyzed according to the regional monitoring indicators and the comprehensive monitoring indicators to obtain the corresponding evaluation deviation data, and the obtained evaluation deviation data are subjected to pixel value mapping processing. According to the pixel value mapping processing result, they are mapped to the corresponding initial equipment image to obtain the corresponding generalized monitoring image.

4. According to the big data-based intelligent management system for mobile Internet operation data according to claim 3, it is characterized in that: The process of generating monitoring visualization images includes: Pre-setting a corresponding classification evaluation system in the corresponding generalized monitoring image, wherein the classification evaluation system includes classification evaluation indicators corresponding to the status of a single device and classification evaluation indicators corresponding to the status of the overall device in the area; According to the classification evaluation system, a single evaluation indicator set and a regional evaluation indicator set are set respectively; The device status data corresponding to the corresponding network device data in the generalized monitoring image is traversed and matched with a single evaluation index set to obtain the corresponding classification results, and the classification results corresponding to the corresponding device status data in the circular management area are quantified and counted, and the quantitative statistical results are traversed and matched with the regional evaluation index set to obtain the classification results of the corresponding circular management area; Identify according to the corresponding classification results, and generate monitoring visualization images based on the identification results.

5. According to the big data-based intelligent management system for mobile Internet operation data according to claim 4, it is characterized in that: The process of generating the corresponding operation coordination data package includes: Sorting the classification results corresponding to the regional evaluation index set and the single evaluation index set according to the corresponding time sequence, performing filling processing based on the time sequence sorting processing results based on the linear difference formula, setting corresponding time series data and signal conversion data for the classification results after the filling processing, and obtaining corresponding periodic feature data according to the corresponding time series data and signal conversion data; Performing statistical analysis on the obtained periodic characteristic data, obtaining q characteristic values ​​corresponding to each unit time, generating a characteristic standard value set, analyzing and processing the characteristic standard value set, and obtaining characteristic evaluation indicators corresponding to the corresponding periodic characteristic data; The obtained monitoring areas are combined and analyzed to generate corresponding control groups. The corresponding periodic characteristic data and characteristic evaluation indicators in each control group are compared and analyzed to obtain the deviation data corresponding to the characteristic evaluation indicators in the corresponding unit time. The corresponding coordination matching data are obtained according to the corresponding deviation data. The coordination matching data of each control group corresponding to the corresponding monitoring area are compared and analyzed. The data are sorted according to the comparison and analysis results to obtain the coordination matching index of the corresponding control group. The operation coordination data packet is generated according to the corresponding coordination matching index.

6. The mobile Internet operation data intelligent management system based on big data according to claim 5 is characterized in that: The process of generating a personalized operation image corresponding to the corresponding monitoring area includes: Obtain the device status data and user behavior data corresponding to the corresponding network device data, analyze and process the user behavior data, obtain the corresponding user behavior data set, analyze and train the user behavior data set based on the deep learning algorithm, and build a corresponding personalized user behavior model; The user behavior data is input into the personalized user behavior model, and the corresponding deviation data is output. The deviation data corresponding to the corresponding time information and the corresponding feature evaluation indicators are visualized to construct the corresponding personalized operation image.

7. The big data-based intelligent management system for mobile Internet operation data according to claim 6, characterized in that: The process of comparing and analyzing the obtained personalized operation image with the corresponding operation coordination data package includes: Perform regional complementary integration on the personalized operation images corresponding to the corresponding monitoring area according to the corresponding feature evaluation indicators, and obtain the corresponding operation coordination data according to the regional complementary integration results; The obtained operation coordination data are weighted with the corresponding coordination matching index in the operation coordination data packet to obtain the priority coordination data of the corresponding monitoring area; Sort and integrate the obtained priority coordination data, obtain the monitoring visualization image corresponding to the corresponding monitoring area according to the sorting and integration results, and set the resource allocation data according to the corresponding equipment status data in the monitoring visualization image and the corresponding Internet base station data; The operation coordination data is dynamically optimized and configured for the resource allocation data corresponding to the corresponding monitoring area according to the corresponding priority coordination data to obtain the corresponding dynamic resource optimization configuration processing result, which is obtained by matching the deviation data corresponding to the corresponding personalized operation image.

8. The mobile Internet operation data intelligent management system based on big data according to claim 7 is characterized in that: The process of intelligently allocating and managing mobile Internet resources in the corresponding monitoring area includes: The dynamic resource optimization configuration processing results are fed back to the intelligent management module corresponding to the corresponding base station equipment. The intelligent management module allocates and manages the operating resource data of the corresponding base station equipment according to the dynamic resource optimization configuration processing results, so that the corresponding mobile Internet equipment in each monitoring area can operate normally.

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