Precise network region division method

Abstract

The invention discloses a network area accurate division method, and relates to the technical field of monitoring analysis, and the method comprises the steps: node data collection: collecting basic information and network state data corresponding to each monitoring node in a target network area; node data analysis: carrying out analysis processing on the basic information and the network state data corresponding to each monitoring node in the target network area, carrying out network fluctuation analysis on the target network area based on an analysis processing result, and formulating an early warning strategy according to a network fluctuation analysis result; the response strategy is used for responding to the early warning strategy and outputting an early warning signal to each monitoring node in the target network area; and fluctuation estimation: estimating the network fluctuation condition of each monitoring node in the target network area in the future time period. The application has the effect of improving the use condition of the network equipment.

Description

Technical Field

[0001] The present application relates to the field of monitoring and analysis technology, and in particular to a method for accurately dividing network areas. Background Art

[0002] With the rapid development of network technology, the Internet has become an indispensable part of people's lives and work. The division of network areas is of great significance for improving the utilization efficiency of network resources, optimizing users' network experience, and ensuring network security. Traditional division methods are difficult to adapt to these rapidly changing network needs, and regional division often relies on static geographic locations or is based on user behavior data.

[0003] In the related art, the existing network area division method cannot be analyzed according to the network status characteristics of the network, which leads to inaccurate network area division, affects the use and optimization of network equipment, and there is room for improvement. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present application provides a method for accurately dividing network areas.

[0005] In the first aspect, the present application provides a method for accurately dividing a network area, which adopts the following technical solution:

[0006] A method for accurately dividing a network area comprises the following steps:

[0007] Node data collection: collect basic information and network status data corresponding to each monitoring node in the target network area;

[0008] Node data analysis: analyzing and processing the basic information and network status data corresponding to each monitoring node in the target network area, performing network fluctuation analysis on the target network area based on the results of the analysis and processing, and formulating an early warning strategy based on the results of the network fluctuation analysis;

[0009] A response strategy, responding to the warning strategy and outputting a warning signal to each monitoring node in the target network area;

[0010] Fluctuation prediction: predict the network fluctuation of each monitoring node in the target network area in the future time period.

[0011] Preferably, the basic information corresponding to each monitoring node in the target network area includes type information, usage information and tag information corresponding to each monitoring node;

[0012] The network status data corresponding to each monitoring node in the target network area includes network transmission rate information, packet loss rate information and delay rate information corresponding to each monitoring node.

[0013] Preferably, the basic information and network status data corresponding to each monitoring node in the target network area are analyzed and processed, specifically including:

[0014] Confirm the basic information corresponding to each monitoring node in the target network area, and extract the usage information corresponding to each monitoring node from the basic information, and confirm the usage time T corresponding to each monitoring node through the usage information corresponding to each monitoring node i and the number of repairs R i , and then through the formula Confirm the usage evaluation coefficient β corresponding to each monitoring node in the target network area i , where i represents the number corresponding to each monitoring node, i = 1, 2, 3.....j, T′ i , R′ i They represent the preset reference usage time and reference maintenance times respectively, and ω1 and ω2 represent the preset weight coefficients;

[0015] By formula The risk coefficient K corresponding to the network fluctuation of each monitoring node in the target network area is calculated. i , where χ i It is represented by the type evaluation coefficient corresponding to the monitoring node numbered i, n i It is represented by the number of markings corresponding to the monitoring node numbered i, and e is a natural constant;

[0016] The risk coefficient K corresponding to the network fluctuation of each monitoring node in the target network area i Compare with the preset risk threshold K′;

[0017] If the network fluctuations occur at each monitoring node in the target network area, the corresponding risk coefficient K i ≤K′, there is no need to perform network fluctuation analysis on each monitoring node in the target network area, and each monitoring node in the target network area is divided into the first network area;

[0018] If there are monitoring nodes in the target network area and network fluctuations occur, the corresponding risk coefficient K i >K′, it is necessary to perform network fluctuation analysis on the monitoring node and divide the monitoring node into the second network area.

[0019] Preferably, performing network fluctuation analysis on the monitoring node specifically includes:

[0020] Confirming the network status data corresponding to each monitoring node in the target network area, and extracting the network transmission rate information, packet loss rate information and delay rate information corresponding to each monitoring node in the target network area from the network status data;

[0021] By formula Confirm the network fluctuation assessment coefficient η corresponding to each monitoring node in the target network area i ;

[0022] Among them, a i 、b i 、c i They represent the network transmission rate assessment coefficient, packet loss rate assessment coefficient, and delay rate assessment coefficient corresponding to the monitoring node numbered i, respectively; a′, b′, and c′ represent the preset reference network transmission rate assessment threshold, reference packet loss rate assessment threshold, and reference delay rate assessment threshold, respectively; ξ1, ξ2, and ξ3 represent the preset weight coefficients;

[0023] The network fluctuation assessment coefficient η corresponding to each monitoring node in the target network area i Compare with the preset network fluctuation assessment threshold η′;

[0024] If there is a network fluctuation assessment coefficient η corresponding to the monitoring node in the target network area i >η′, it is necessary to formulate an early warning strategy for the monitoring node and divide the monitoring node into the third network area.

[0025] Preferably, the process of formulating an early warning strategy for the monitoring node specifically includes:

[0026] By formula M i =φ1*(K i -K′)+φ2*(η i -η′), and calculate the comprehensive reference value M corresponding to each monitoring node in the target network area i , where φ1 and φ2 represent the preset correlation coefficients;

[0027] The comprehensive reference value M corresponding to each monitoring node in the target network area i Compare with the preset comprehensive reference threshold M′,

[0028] If there is a comprehensive reference value M corresponding to the monitoring node in the target network area i ≤M′, a first-level warning signal needs to be output for the monitoring node;

[0029] If there is a comprehensive reference value M corresponding to the monitoring node in the target network area i >M′, a second-level warning signal needs to be output to the monitoring node, wherein the warning level of the second-level warning signal is greater than that of the first-level warning signal.

[0030] Preferably, the process of obtaining the marking times specifically includes:

[0031] Collect the temperature values ​​corresponding to each monitoring node in the target network area in real time to form a time series, and use the function Temi (t) means;.

[0032] By formula Confirm the temperature evaluation coefficient corresponding to each monitoring node in the target network area Wherein, tem(t) represents the preset standard temperature change curve, and Tem′ represents the preset standard temperature value;

[0033] The temperature evaluation coefficient corresponding to each monitoring node in the target network area Preset temperature assessment thresholds Make a comparison;

[0034] If there is a temperature evaluation coefficient corresponding to the monitoring node in the target network area Then the monitoring node needs to be marked once, otherwise, it does not need to be marked.

[0035] Preferably, the network fluctuation situation of each monitoring node in the target network area in the future time period is estimated, specifically including:

[0036] Confirm the comprehensive reference value corresponding to each monitoring node in the target network area, and establish the real-time change curve of the comprehensive reference value of each monitoring node M i (t);

[0037] By formula Confirm the change coefficient D of the comprehensive reference value of each monitoring node in the target network area i , where f a Represented as a preset definition function, They are respectively expressed as the maximum and minimum values ​​of the comprehensive reference value;

[0038] The variation coefficient D of the comprehensive reference value of each monitoring node in the target network area i Compare with the preset change threshold D′;

[0039] If the target network area has a change coefficient D of the comprehensive reference value of the monitoring node i >D′, it is determined that the risk value of the monitoring node in the future time period increases, and the staff is warned to strengthen management.

[0040] In the second aspect, the present application provides a network area precise division system, which adopts the following technical solutions:

[0041] A network area precise division system, comprising:

[0042] A data collection module is used to collect network status data corresponding to each monitoring node in the target network area;

[0043] A data analysis module is used to analyze and process the network status data corresponding to each monitoring node in the target network area, perform network fluctuation analysis on the target network area based on the analysis results, and formulate a regional division strategy according to the analysis results of the network fluctuations;

[0044] A response strategy module, used to respond to the area division strategy and output a fluctuation warning signal to each monitoring node in the target network area;

[0045] The fluctuation prediction module is used to predict the network fluctuation of each monitoring node in the target network area in the future time period.

[0046] In a third aspect, the present application provides a computer-readable storage medium storing instructions, which, when executed on a computer, enables the computer to execute any one of the above-described methods for accurately dividing a network area.

[0047] In summary, the present application includes at least one of the following beneficial technical effects:

[0048] 1. The present invention provides a method for accurately dividing network areas. By analyzing and processing the basic information corresponding to each monitoring node in the target network area, the risk coefficient corresponding to the network fluctuation of each monitoring node in the target network area is confirmed, and the risk coefficient corresponding to the network fluctuation of each monitoring node in the target network area is compared with a preset risk threshold. Based on the comparison result, each monitoring node is divided into different network areas, thereby effectively improving the accuracy of network area division, thereby effectively optimizing the use of network equipment;

[0049] 2. By analyzing and processing the network status data corresponding to each monitoring node in the target network area, the network fluctuation assessment coefficient corresponding to each monitoring node in the target network area is confirmed, the network fluctuation assessment coefficient corresponding to each monitoring node in the target network area is compared with the preset network fluctuation assessment threshold, and the monitoring node is divided into the third network area based on the comparison result, which further effectively improves the accuracy of network area division;

[0050] 3. By collecting the temperature values ​​corresponding to each monitoring node in the target network area, the temperature evaluation coefficient corresponding to each monitoring node in the target network area is confirmed, and then the monitoring nodes are marked based on the temperature evaluation coefficient corresponding to each monitoring node, thereby effectively improving the authenticity and validity of the data source, thereby effectively optimizing the use of network equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0052] Figure 1 It is a flow chart of the method for accurate division of network areas in an embodiment of the present application.

[0053] Figure 2 It is a system diagram of precise division of network areas in an embodiment of the present application. DETAILED DESCRIPTION

[0054] The following is combined with Figure 1-2 This application is described in further detail.

[0055] Example 1

[0056] The embodiment of the present application discloses a method for accurately dividing network areas.

[0057] Reference Figure 1 , a method for accurately dividing a network area, comprising the following steps:

[0058] Node data collection: collect basic information and network status data corresponding to each monitoring node in the target network area;

[0059] Node data analysis: analyzing and processing the basic information and network status data corresponding to each monitoring node in the target network area, performing network fluctuation analysis on the target network area based on the results of the analysis and processing, and formulating an early warning strategy based on the results of the network fluctuation analysis;

[0060] A response strategy, responding to the warning strategy and outputting a warning signal to each monitoring node in the target network area;

[0061] Fluctuation prediction: predict the network fluctuation of each monitoring node in the target network area in the future time period.

[0062] Furthermore, the basic information corresponding to each monitoring node in the target network area includes type information, usage information and tag information corresponding to each monitoring node;

[0063] The network status data corresponding to each monitoring node in the target network area includes network transmission rate information, packet loss rate information and delay rate information corresponding to each monitoring node.

[0064] Specifically, in the embodiment of the present application, each monitoring node in the target network area includes but is not limited to a sensor node, a gateway, and a router.

[0065] It should be noted that the basic information and network status data corresponding to each monitoring node in the target network area are analyzed and processed, specifically including:

[0066] Confirm the basic information corresponding to each monitoring node in the target network area, and extract the usage information corresponding to each monitoring node from the basic information, and confirm the usage time T corresponding to each monitoring node through the usage information corresponding to each monitoring node i and the number of repairs R i , and then through the formula Confirm the usage evaluation coefficient β corresponding to each monitoring node in the target network area i , where i represents the number corresponding to each monitoring node, i = 1, 2, 3.....j, T′ i , R′ i They represent the preset reference usage time and reference maintenance times respectively, and ω1 and ω2 represent the preset weight coefficients;

[0067] By formula The risk coefficient K corresponding to the network fluctuation of each monitoring node in the target network area is calculated. i , where χ i It is represented by the type evaluation coefficient corresponding to the monitoring node numbered i, n i It is represented by the number of markings corresponding to the monitoring node numbered i, and e is a natural constant;

[0068] The risk coefficient K corresponding to the network fluctuation of each monitoring node in the target network area i Compare with the preset risk threshold K′;

[0069] If the network fluctuations occur at each monitoring node in the target network area, the corresponding risk coefficient K i ≤K′, there is no need to perform network fluctuation analysis on each monitoring node in the target network area, and each monitoring node in the target network area is divided into the first network area;

[0070] If there are monitoring nodes in the target network area and network fluctuations occur, the corresponding risk coefficient K i >K′, it is necessary to perform network fluctuation analysis on the monitoring node and divide the monitoring node into the second network area.

[0071] Specifically, different type assessment coefficients of monitoring nodes have different degrees of influence on network stability. Combining the type assessment coefficient and the usage assessment coefficient can accurately judge the overall performance of each monitoring node. In terms of network fluctuations, the number of markings is an indicator that reflects the frequency of problems encountered by the monitoring node. The higher the number of markings, the higher the probability of network fluctuations at the monitoring node. The risk coefficient of network fluctuations for each monitoring node is calculated by comprehensively considering the type assessment coefficient, the number of markings and the usage assessment coefficient of the monitoring node. The risk coefficient can effectively indicate the risk of the monitoring node encountering network fluctuations. Using the risk coefficient, staff can more accurately identify and prevent potential network problems, thereby taking measures in advance to avoid network service interruptions or performance degradation.

[0072] It should be noted that the network fluctuation analysis of the monitoring node specifically includes:

[0073] Confirming the network status data corresponding to each monitoring node in the target network area, and extracting the network transmission rate information, packet loss rate information and delay rate information corresponding to each monitoring node in the target network area from the network status data;

[0074] By formula Confirm the network fluctuation assessment coefficient η corresponding to each monitoring node in the target network area i ;

[0075] Among them, a i 、b i 、c i They represent the network transmission rate assessment coefficient, packet loss rate assessment coefficient, and delay rate assessment coefficient corresponding to the monitoring node numbered i, respectively; a′, b′, and c′ represent the preset reference network transmission rate assessment threshold, reference packet loss rate assessment threshold, and reference delay rate assessment threshold, respectively; ξ1, ξ2, and ξ3 represent the preset weight coefficients;

[0076] The network fluctuation assessment coefficient η corresponding to each monitoring node in the target network area i Compare with the preset network fluctuation assessment threshold η′;

[0077] If there is a network fluctuation assessment coefficient η corresponding to the monitoring node in the target network area i >η′, it is necessary to formulate an early warning strategy for the monitoring node, and divide the monitoring node into a third network area, and the network performance of the network area is from high to low: the first network area> the second network area> the third network area.

[0078] Specifically, by monitoring the network transmission rate information, packet loss rate information and delay rate information of the node, determining the network fluctuation assessment coefficient can accurately reflect the fluctuation of network performance in real time, thereby helping staff to quickly locate the source of the problem, optimize the network configuration, prevent potential network failures in advance, and ensure the continuity of network services and the quality of user experience.

[0079] It should be noted that the process of formulating an early warning strategy for the monitoring node specifically includes:

[0080] By formula M i =φ1*(K i -K′)+φ2*(η i -η′), and calculate the comprehensive reference value M corresponding to each monitoring node in the target network area i , where φ1 and φ2 represent the preset correlation coefficients;

[0081] The comprehensive reference value M corresponding to each monitoring node in the target network area i Compare with the preset comprehensive reference threshold M′,

[0082] If there is a comprehensive reference value M corresponding to the monitoring node in the target network area i ≤M′, a first-level warning signal needs to be output for the monitoring node;

[0083] If there is a comprehensive reference value M corresponding to the monitoring node in the target network area i >M′, a second-level warning signal needs to be output to the monitoring node, wherein the warning level of the second-level warning signal is greater than that of the first-level warning signal.

[0084] Furthermore, the process of obtaining the number of markings specifically includes:

[0085] Collect the temperature values ​​corresponding to each monitoring node in the target network area in real time to form a time series, and use the function Tem i (t) means;.

[0086] By formula Confirm the temperature evaluation coefficient corresponding to each monitoring node in the target network area Wherein, tem(t) represents the preset standard temperature change curve, and Tem′ represents the preset standard temperature value;

[0087] The temperature evaluation coefficient corresponding to each monitoring node in the target network area Preset temperature assessment thresholds Make a comparison;

[0088] If there is a temperature evaluation coefficient corresponding to the monitoring node in the target network area Then the monitoring node needs to be marked once, otherwise, it does not need to be marked.

[0089] Specifically, the temperature assessment coefficient of each monitoring node in the target network area is established and marked accordingly, helping staff to monitor and identify equipment that may have performance degradation or potential failures due to excessive temperature in real time, and then take cooling measures or perform maintenance to prevent equipment damage and network interruption, thereby improving the stability and reliability of the entire network system.

[0090] Furthermore, the network fluctuations of each monitoring node in the target network area in the future time period are estimated, including:

[0091] Confirm the comprehensive reference value corresponding to each monitoring node in the target network area, and establish the real-time change curve of the comprehensive reference value of each monitoring node M i (t);

[0092] By formula Confirm the change coefficient D of the comprehensive reference value of each monitoring node in the target network area i , where f a Represented as a preset definition function, They are respectively expressed as the maximum and minimum values ​​of the comprehensive reference value;

[0093] The variation coefficient D of the comprehensive reference value of each monitoring node in the target network area i Compare with the preset change threshold D′;

[0094] If the target network area has a change coefficient D of the comprehensive reference value of the monitoring node i >D′, it is determined that the risk value of the monitoring node in the future time period increases, and the staff is warned to strengthen management.

[0095] Example 2

[0096] The embodiment of the present application also discloses a system for accurately dividing network areas.

[0097] Reference Figure 2 , a network area precise division system, comprising:

[0098] A data collection module is used to collect network status data corresponding to each monitoring node in the target network area;

[0099] A data analysis module is used to analyze and process the network status data corresponding to each monitoring node in the target network area, perform network fluctuation analysis on the target network area based on the analysis results, and formulate a regional division strategy according to the analysis results of the network fluctuations;

[0100] A response strategy module, used to respond to the area division strategy and output a fluctuation warning signal to each monitoring node in the target network area;

[0101] The fluctuation prediction module is used to predict the network fluctuation of each monitoring node in the target network area in the future time period.

[0102] The above contents are merely examples and explanations of the concept of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

[0103] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0104] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for accurately dividing a network area, characterized in that: The following steps are involved: Node data collection: collect basic information and network status data corresponding to each monitoring node in the target network area; Node data analysis: analyzing and processing the basic information and network status data corresponding to each monitoring node in the target network area, performing network fluctuation analysis on the target network area based on the results of the analysis and processing, and formulating an early warning strategy based on the results of the network fluctuation analysis; A response strategy, responding to the warning strategy and outputting a warning signal to each monitoring node in the target network area; Fluctuation prediction: predict the network fluctuation of each monitoring node in the target network area in the future time period.

2. A method for accurately dividing a network area according to claim 1, characterized in that: The basic information corresponding to each monitoring node in the target network area includes type information, usage information and tag information corresponding to each monitoring node; The network status data corresponding to each monitoring node in the target network area includes network transmission rate information, packet loss rate information and delay rate information corresponding to each monitoring node.

3. A method for accurately dividing a network area according to claim 2, characterized in that: Analyze and process the basic information and network status data corresponding to each monitoring node in the target network area, including: Confirm the basic information corresponding to each monitoring node in the target network area, and extract the usage information corresponding to each monitoring node from the basic information. Confirm the usage time Ti and maintenance times Ri corresponding to each monitoring node through the usage information corresponding to each monitoring node, and then use the formula Confirm the usage evaluation coefficient βi corresponding to each monitoring node in the target network area, where i represents the number corresponding to each monitoring node, i=1,2,3.....j, Ti′ and Ri′ represent the preset reference usage time and reference maintenance times respectively, and ω1 and ω2 represent the preset weight coefficients; By formula The risk coefficient Ki corresponding to the network fluctuation of each monitoring node in the target network area is calculated, where χi represents the type assessment coefficient corresponding to the monitoring node numbered i, ni represents the number of markings corresponding to the monitoring node numbered i, and e is a natural constant; Compare the risk coefficient Ki corresponding to the network fluctuation of each monitoring node in the target network area with the preset risk threshold K′; If the risk coefficient Ki≤K′ corresponding to the network fluctuation occurs in each monitoring node in the target network area, there is no need to perform network fluctuation analysis on each monitoring node in the target network area, and each monitoring node in the target network area is divided into the first network area; If there is a monitoring node in the target network area with a risk coefficient Ki>K′ corresponding to network fluctuation, it is necessary to perform a network fluctuation analysis on the monitoring node and divide the monitoring node into the second network area.

4. A method for accurately dividing a network area according to claim 3, characterized in that: Performing network fluctuation analysis on the monitoring node specifically includes: Confirming the network status data corresponding to each monitoring node in the target network area, and extracting the network transmission rate information, packet loss rate information and delay rate information corresponding to each monitoring node in the target network area from the network status data; By formula Confirm the network fluctuation assessment coefficient ηi corresponding to each monitoring node in the target network area; Wherein, ai, bi, ci represent the network transmission rate assessment coefficient, packet loss rate assessment coefficient, and delay rate assessment coefficient corresponding to the monitoring node numbered i, respectively; a′, b′, c′ represent the preset reference network transmission rate assessment threshold, reference packet loss rate assessment threshold, and reference delay rate assessment threshold, respectively; ξ1, ξ2, ξ3 represent the preset weight coefficients; Compare the network fluctuation assessment coefficient ηi corresponding to each monitoring node in the target network area with the preset network fluctuation assessment threshold η′; If there is a network fluctuation assessment coefficient ηi>η′ corresponding to a monitoring node in the target network area, it is necessary to formulate an early warning strategy for the monitoring node and divide the monitoring node into the third network area.

5. A method for accurately dividing a network area according to claim 4, characterized in that: The process of formulating an early warning strategy for the monitoring node specifically includes: The comprehensive reference value Mi corresponding to each monitoring node in the target network area is calculated by the formula Mi=φ1*(Ki-K′)+φ2*(ηi-η′), where φ1 and φ2 represent the preset correlation coefficients; Compare the comprehensive reference value Mi corresponding to each monitoring node in the target network area with the preset comprehensive reference threshold M′. If there is a comprehensive reference value Mi≤M′ corresponding to a monitoring node in the target network area, a first-level warning signal needs to be output for the monitoring node; If there is a comprehensive reference value Mi>M′ corresponding to a monitoring node in the target network area, a second-level warning signal needs to be output to the monitoring node, wherein the warning level of the second-level warning signal is greater than that of the first-level warning signal.

6. A method for accurately dividing a network area according to claim 2, characterized in that: The process of obtaining the number of markings includes: The temperature values ​​corresponding to each monitoring node in the target network area are collected in real time to form a time series, and the temperature values ​​are represented by the function Temi(t) according to the time series; By formula Confirm the temperature evaluation coefficient corresponding to each monitoring node in the target network area Wherein, tem(t) represents the preset standard temperature change curve, and Tem′ represents the preset standard temperature value; The temperature evaluation coefficient corresponding to each monitoring node in the target network area Preset temperature assessment thresholds Make a comparison; If there is a temperature evaluation coefficient corresponding to the monitoring node in the target network area Then the monitoring node needs to be marked once, otherwise, it does not need to be marked.

7. A method for accurately dividing a network area according to claim 5, characterized in that: Estimate the network fluctuations of each monitoring node in the target network area in the future time period, including: Confirm the comprehensive reference value corresponding to each monitoring node in the target network area, and establish the real-time change curve Mi(t) of the comprehensive reference value of each monitoring node; By formula Confirm the variation coefficient Di of the comprehensive reference value of each monitoring node in the target network area, where fa represents a preset definition function, Mimax and Mimin represent the maximum and minimum values ​​of the comprehensive reference value respectively; Compare the change coefficient Di of the comprehensive reference value of each monitoring node in the target network area with the preset change threshold D′; If there is a change coefficient Di>D′ of the comprehensive reference value of the monitoring node in the target network area, it is determined that the risk value of the monitoring node will increase in the future time period, and the staff is warned to strengthen management.

8. A network area precise division system, applied to a network area precise division method according to claims 1 to 7, characterized in that: include: A data collection module is used to collect network status data corresponding to each monitoring node in the target network area; A data analysis module is used to analyze and process the network status data corresponding to each monitoring node in the target network area, perform network fluctuation analysis on the target network area based on the analysis results, and formulate a regional division strategy according to the analysis results of the network fluctuations; A response strategy module, used to respond to the area division strategy and output a fluctuation warning signal to each monitoring node in the target network area; The fluctuation prediction module is used to predict the network fluctuation of each monitoring node in the target network area in the future time period.

9. A computer-readable storage medium, characterized in that: Instructions are stored, and when the instructions are executed on a computer, the computer executes a method for accurately dividing a network area as described in any one of claims 1 to 7.

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