Campus network traffic prediction method and system

Abstract

The application discloses a campus network flow prediction method and system, relates to the technical field of flow prediction, and comprises the following steps: step one, historical flow analysis, step two, flow distribution and step three, flow scheduling. The flow information of each region in each time period in each historical preset period is analyzed, the total demand of the current period campus flow is predicted, the flow priority and the flow threshold of each region in each time period are obtained, the flow distribution of each region is carried out based on the flow priority of each region in each time period, the speed of each region in each time period is analyzed when the flow threshold is reached, the network management strategy is refined, the flow resource is dynamically adjusted, the network resource utilization is greatly improved, and finally, the flow of each region in each time period is scheduled, so that the on-demand distribution and dynamic optimization of the campus flow are ensured.

Description

Technical Field

[0001] This application relates to the field of traffic prediction technology, specifically to a method and system for predicting campus network traffic. Background Technology

[0002] Today, campus networks have become a core tool for supporting educational informatization in universities. University network administrators need to comprehensively monitor network traffic status, understand operational conditions in a timely manner, identify potential problems early, and take corrective measures. Therefore, accurate and effective network traffic prediction and adjustment are of great significance for improving the management quality and service efficiency of campus networks, maintaining their stability and reliability, and many other aspects. Therefore, this application proposes a campus network traffic prediction method and system.

[0003] The prior art, such as the invention application patent with announcement number CN113055923B, discloses a mobile network traffic prediction method, apparatus, and device. The method includes: acquiring historical mobile network data within a target time period; inputting the historical mobile network data into a traffic prediction model to obtain the output result of the traffic prediction model; determining the weights corresponding to each of the traffic prediction models; and calculating the traffic prediction result for the time to be predicted based on the output result of each traffic prediction model and the weights.

[0004] The above-mentioned solution has the following technical problems: 1. The current technology only predicts the traffic at the time of prediction based on historical mobile network data, without considering how to allocate and adjust the traffic in each prediction time period when traffic data is insufficient. The current technology's neglect of this aspect leads to its lack of perfection and comprehensiveness.

[0005] 2. Current technology does not consider how to allocate and adjust traffic data in different regions when traffic data is insufficient, nor does it consider how to adjust traffic between regions when traffic data in a certain region exceeds the limit at a certain predicted time, so as to ensure the normal operation of each region. The current technology's neglect of this aspect may lead to a decrease in network performance in each region when traffic exceeds the limit, thereby increasing the workload. Summary of the Invention

[0006] The purpose of this application is to provide a campus network traffic prediction method and system, which solves the problems existing in the background technology.

[0007] To solve the above-mentioned technical problems, this application adopts the following technical solution: In the first aspect, this application provides a campus network traffic prediction method, including: Step 1, historical traffic analysis: obtain traffic usage information in the campus from the information and network center, then predict the total traffic demand for the current preset period, and analyze the traffic priority of each area in each time period, and at the same time analyze the traffic threshold of each area in each time period.

[0008] Step 2, Traffic Allocation: Based on the traffic priority of each region in each time period, traffic is allocated to each region in the current preset period, and the traffic type of each region in each time period is monitored. When the traffic threshold is reached, the traffic in each region in each time period is rate-limited based on the traffic type.

[0009] Step 3: Traffic scheduling: When traffic is insufficient, traffic scheduling is performed for each time period and region.

[0010] In a second aspect, this application provides a campus network traffic prediction system, including: a historical traffic analysis module, a traffic allocation module, and a traffic scheduling module.

[0011] Historical Traffic Analysis Module: This module is used to obtain traffic usage information from the Information and Network Center on campus, and then predict the total traffic demand for the current preset period. It also analyzes and obtains the traffic priority for each region in each time period, as well as the traffic threshold for each region in each time period.

[0012] Traffic allocation module: It is used to allocate traffic to each region in the current preset period according to the traffic priority of each time period and region, and monitor the traffic type of each time period and region. When the traffic threshold is reached, the traffic in each time period and region is rate-limited based on the traffic type.

[0013] Traffic scheduling module: Used to schedule traffic for different time periods and regions when traffic is insufficient.

[0014] The beneficial effects of this application are as follows: 1. The campus network traffic prediction method and system provided by this application analyzes the traffic information of each time period and each region in each historical preset period, thereby predicting the total campus traffic demand in the current period. At the same time, it analyzes and obtains the traffic priority and traffic threshold of each time period and each region, and then allocates traffic to each region based on the traffic priority of each time period and each region. When the traffic threshold is reached, it performs speed limiting analysis on each time period and each region. Based on this, through a refined network management strategy, it dynamically adjusts traffic resources, greatly improving the network resource utilization rate. Finally, it performs traffic scheduling on each time period and each region to ensure on-demand allocation and dynamic optimization of campus traffic.

[0015] 2. This application obtains traffic information from each historical preset period, providing a data basis for predicting the total campus traffic demand in the current period, and also laying the foundation for traffic priority and traffic threshold analysis in each time period and region.

[0016] 3. This application allocates traffic to each region based on the traffic priority of each time period and region, thereby establishing a refined network management strategy, dynamically adjusting traffic resources, greatly improving network resource utilization, and limiting the rate of each region and time period when the traffic threshold is reached, thereby ensuring the stability of critical services and avoiding system paralysis caused by traffic overload. Finally, traffic scheduling for each region and time period ensures on-demand allocation and dynamic optimization of campus traffic. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating the steps involved in implementing the method described in this application.

[0019] Figure 2 This is a schematic diagram of the system structure connection of this application. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] Reference Figure 1 As shown, this application provides a campus network traffic prediction method in the first aspect, including the following steps: Step 1, historical traffic analysis: obtain traffic usage information in the campus from the information and network center, and then predict the total traffic demand for the current preset period, and analyze the traffic priority of each area in each time period, and at the same time analyze the traffic threshold of each area in each time period.

[0022] It should be noted that the specific length of the preset period is set by the relevant staff, and can be one day, one week, or one month, with specific limitations here.

[0023] In a specific example, the traffic usage information includes the bandwidth threshold and total traffic usage for each region in each historical preset period, wherein the bandwidth threshold includes an upper limit and a lower limit.

[0024] In a specific example, the process of predicting the total traffic demand for the current preset period is as follows: According to a preset ratio, the traffic monitoring data of each time period and each region in each historical preset period are divided into a dataset and a prediction set. A network traffic VMD-PSO-Bi LSTM prediction model is constructed based on the dataset. The prediction set is used as the data source and input into the network traffic VMD-PSO-Bi LSTM prediction model. The total campus traffic demand for the current preset period is predicted by the network traffic VMD-PSO-Bi LSTM prediction model.

[0025] It should be noted that the preset ratio is set by the relevant staff and no specific restrictions are imposed here.

[0026] It should be noted that the construction method of the network traffic VMD-PSO-Bi LSTM prediction model and the traffic prediction based on the network traffic VMD-PSO-BiLSTM prediction model are existing technologies, and therefore will not be described in detail.

[0027] In a specific example, the analysis yields traffic priorities for each time period and region. The specific analysis process is as follows: Based on traffic usage information on campus, the bandwidth thresholds for each time period and region within each historical preset period are obtained, and then the traffic rate demand assessment coefficients for each time period and region are analyzed and obtained. Where i represents the number of each time period, i is a positive integer, and j represents the number of each region, j is a positive integer.

[0028] Based on campus traffic usage information, the total traffic usage of each area in each time period of each historical preset period is obtained, and then the traffic demand assessment coefficient for each area in each time period is obtained through analysis.

[0029] Input the traffic rate demand assessment coefficient and traffic usage demand assessment coefficient for each time period and region into the traffic classification model, and then, based on the traffic classification model expression:

[0030] Output the flow demand characteristic value η for region j within time period i. ijχ′ and χ″ are the lower and upper limits of the comprehensive traffic demand assessment coefficient, respectively. A certain area in a certain time period with a traffic demand characteristic value of 1 is designated as a first-level traffic priority area, a certain area in a certain time period with a traffic demand characteristic value of 0 is designated as a second-level traffic priority area, and a certain area in a certain time period with a traffic demand characteristic value of -1 is designated as a third-level traffic priority area. Based on this, the first-level traffic priority areas, second-level traffic priority areas, and third-level traffic priority areas for each time period are obtained.

[0031] It should be noted that when the traffic demand characteristic value is 1, it indicates that the traffic demand is relatively large; when the traffic demand characteristic value is 0, it indicates that the traffic demand is moderate; and when the traffic demand characteristic value is -1, it indicates that the traffic demand is low.

[0032] It should be noted that the lower and upper limits of the comprehensive traffic demand assessment coefficient are set by the relevant staff. For example, the lower limit of the comprehensive traffic demand assessment coefficient can be set to 2 and the upper limit to 5. When the comprehensive traffic demand assessment coefficient is 3, 2 < 3 < 5, the traffic characteristic value is 0, and the corresponding area is the secondary traffic priority area.

[0033] In a specific example, the traffic rate demand assessment coefficient and traffic usage demand assessment coefficient for each region in each time period are analyzed and obtained. The specific analysis process is as follows: The bandwidth threshold for each region in each time period of each historical preset period is denoted as... and in and These are the upper and lower bandwidth limits, calculated using the following formula: The analysis yielded the flow rate demand assessment coefficient for region j within time period i. Where E represents the total number of historical preset periods, and W′ represents the set bandwidth standard value.

[0034] It should be noted that the bandwidth standard value is set by the network operator according to different network packages, such as 100Mbps and 500Mbps.

[0035] The total traffic usage for each time period and region within each historical preset period is recorded as follows: According to the calculation formula: The analysis yielded the traffic demand assessment coefficient for region j within time period i. Where Q′ ij This indicates the set standard value for total traffic usage.

[0036] It should be noted that the standard value of total traffic usage is set by the Information and Network Technology Center. For example, the average value of total traffic usage for each region in each time period corresponding to each historical period is recorded as the standard value of total traffic usage for each region in each time period.

[0037] In a specific example, the analysis obtains the traffic thresholds for each region in each time period. The specific analysis process is as follows: Based on the traffic usage information in the campus, the total traffic usage of each region in each time period of each historical preset cycle is obtained. The total traffic usage of a certain region in a certain time period of each historical preset cycle is distributed normally. The median value after the normal distribution is recorded as the secondary traffic threshold of the region in that time period, and the maximum value after the normal distribution is recorded as the primary traffic threshold of the region in that time period. Based on this, the primary traffic threshold and secondary traffic threshold of each region in each time period are obtained.

[0038] Step 2, Traffic Allocation: Based on the traffic priority of each region in each time period, traffic is allocated to each region in the current preset period, and the traffic type of each region in each time period is monitored. When the traffic threshold is reached, the traffic in each region in each time period is rate-limited based on the traffic type.

[0039] In a specific example, the process of allocating traffic to each region in the current preset period based on the traffic priority of each time period is as follows: Combining the traffic usage demand assessment coefficient and the traffic rate demand assessment coefficient of each region in each time period, according to the calculation formula:

[0040] The comprehensive traffic demand assessment coefficient of the j-th region is obtained through analysis, where I is the total number of each time period. Then, the ratio of the comprehensive traffic demand assessment coefficients of each region is calculated. Based on the ratio of the comprehensive traffic demand assessment coefficients of each region, the traffic of the current information and network center is allocated to obtain the matching traffic of each region in the current preset period.

[0041] Based on the combined assessment coefficients for traffic volume demand and traffic rate demand in different time periods and regions, according to the calculation formula: The comprehensive traffic demand assessment coefficient of the j-th region in the i-th time period is obtained by analysis. Then, the ratio of the comprehensive traffic demand assessment coefficient of each region in each time period is calculated. Based on the ratio of the comprehensive traffic demand assessment coefficient of each region in each time period, the matching traffic of each region is secondary allocated to obtain the matching traffic of each region in each time period.

[0042] In a specific example, the process of limiting the traffic flow in each region and time period based on the traffic type is as follows: monitoring the traffic usage in each region and time period, and obtaining the traffic usage type and total traffic usage in each region and time period based on the traffic usage monitoring results.

[0043] It should be noted that the traffic usage types include traffic characteristic of education and scientific research applications, traffic characteristic of high-bandwidth applications, and traffic characteristic of social and utility applications. Among them, traffic characteristic of high-bandwidth applications refers to applications used in video media and online games, traffic characteristic of education and scientific research applications includes virtual simulation experimental platforms, online examination systems, remote collaboration tools, and file transfer, and traffic characteristic of social and utility applications includes social software, instant messaging, and email.

[0044] When the total traffic usage in a certain area reaches the first-level traffic threshold of that area within a certain time period, the traffic priority of that area within that time period is obtained based on the traffic priority of each area within each time period. The traffic usage type of that area within that time period is then obtained based on the traffic usage type of each area within that time period. Based on the traffic usage type of that area within that time period, characteristic traffic of education and scientific research applications, characteristic traffic of high-bandwidth applications, and characteristic traffic of social and tool applications are obtained. First-level rate limiting is applied to characteristic traffic of education and scientific research applications, while second-level rate limiting is applied to characteristic traffic of high-bandwidth applications and characteristic traffic of social and tool applications.

[0045] When the traffic usage in a certain area reaches the secondary traffic threshold of that area during a certain period, the traffic characteristic of education and scientific research applications is subject to primary rate limiting, the traffic characteristic of social and utility applications is subject to secondary rate limiting, and the traffic characteristic of high-bandwidth applications is subject to tertiary rate limiting.

[0046] The first-level speed limiting process is to not limit the speed, the third-level speed limiting process is to disconnect the traffic, and the second-level speed limiting process is to limit the speed to half of the original bandwidth.

[0047] Step 3: Traffic scheduling: When traffic is insufficient, traffic scheduling is performed for each time period and region.

[0048] In a specific example, the traffic scheduling for each region and time period is carried out as follows: Based on the traffic monitoring results of each region and time period in the current preset period, the total traffic usage of each region and time period up to the current time point is obtained. If the total traffic usage of a region and time period up to the current time point reaches the total matching traffic of that region and time period, the traffic priority of that region and the traffic priority of other regions and time period are obtained. Then, regions with lower traffic priorities than that region and time period are obtained and recorded as matching regions. The remaining traffic of each matching region and time period up to the current time point is sorted in descending order. Traffic scheduling is carried out for the region according to the sorting result, and the sorting result is updated in real time based on the scheduling result.

[0049] It should be noted that traffic scheduling is prioritized for each matching region with a high ranking.

[0050] Reference Figure 2As shown, this application provides a campus network traffic prediction system in a second aspect, including the following modules: a historical traffic analysis module, a traffic allocation module, and a traffic scheduling module.

[0051] Historical Traffic Analysis Module: This module is used to obtain traffic usage information from the Information and Network Center on campus, and then predict the total traffic demand for the current preset period. It also analyzes and obtains the traffic priority for each region in each time period, as well as the traffic threshold for each region in each time period.

[0052] Traffic allocation module: It is used to allocate traffic to each region in the current preset period according to the traffic priority of each time period and region, and monitor the traffic type of each time period and region. When the traffic threshold is reached, the traffic in each time period and region is rate-limited based on the traffic type.

[0053] Traffic scheduling module: Used to schedule traffic for different time periods and regions when traffic is insufficient.

[0054] This application provides a campus network traffic prediction method and system. By analyzing traffic information of each time period and region in each historical preset period, it can predict the total campus traffic demand in the current period. At the same time, it analyzes the traffic priority and traffic threshold of each time period and region, and then allocates traffic to each region based on the traffic priority of each time period and region. When the traffic threshold is reached, it performs rate limiting analysis on each time period and region. Based on this, through a refined network management strategy, it dynamically adjusts traffic resources, which greatly improves the network resource utilization rate. Finally, it performs traffic scheduling for each time period and region to ensure on-demand allocation and dynamic optimization of campus traffic.

[0055] The above content is merely an example and illustration of the concept of this application. Those skilled in the art can make various modifications or additions to the specific embodiments described or use similar methods to replace them, as long as they do not deviate from the inventive concept or exceed the scope defined in this application, they should all fall within the protection scope of this application.

Claims

1. A method for campus network traffic prediction, characterized in that, The application relates to a network traffic scheduling method and device. Step one, historical traffic analysis: obtaining traffic usage information in a campus from an information and network center, then predicting a total traffic demand amount in a current preset period, and analyzing traffic priorities of each region in each time period and each traffic threshold value of each region in each time period; The traffic usage information comprises bandwidth threshold values and total traffic usage amounts of each region in each time period in each historical preset period, wherein the bandwidth threshold values comprise upper and lower bandwidth limit values; The total traffic demand amount in the current preset period is predicted in the following manner: the traffic monitoring data of each region in each time period in each historical preset period is divided into a data set and a prediction set according to a preset proportion, a network traffic VMD-PSO-BiLSTM prediction model is constructed according to the data set, the prediction set is input into the network traffic VMD-PSO-BiLSTM prediction model as a data source, and the total campus traffic demand amount in the current preset period is predicted by the network traffic VMD-PSO-BiLSTM prediction model; The analysis obtains the flow priority of each area in each time period, and the specific analysis process is as follows: based on the flow usage information in the campus, the bandwidth threshold of each area in each time period in each historical preset period is obtained, and then the flow rate demand evaluation coefficient of each area in each time period is obtained Wherein i represents the number of each time period, i is a positive integer, j represents the number of each area, and j is a positive integer; Based on the traffic usage information in the campus, the total traffic usage amount of each region in each time period in each historical preset period is obtained, and then a traffic usage demand evaluation coefficient of each region in each time period is obtained through analysis The flow rate demand evaluation coefficient and the flow usage demand evaluation coefficient of each region in each time period are input into the flow grading model, and the flow demand characteristic value η of the region numbered j in the time period numbered i is output according to the expression of the flow grading model: The flow demand characteristic value η of the region numbered j in the time period numbered i is output according to the expression of the flow grading model: ij wherein χ' and χ'' are respectively the lower limit value and the upper limit value of the flow comprehensive demand evaluation coefficient, a region in a time period with the flow demand characteristic value of 1 is recorded as a first-level flow priority region, a region in a time period with the flow demand characteristic value of 0 is recorded as a second-level flow priority region, and a region in a time period with the flow demand characteristic value of -1 is recorded as a third-level flow priority region, and thus the first-level flow priority regions, the second-level flow priority regions and the third-level flow priority regions in each time period are obtained. The analysis obtains the flow rate demand evaluation coefficient and the flow consumption demand evaluation coefficient of each area in each time period, and the specific analysis process is as follows: the bandwidth threshold of each area in each time period in each historical preset period is denoted as W' ij e and W" ij e , wherein W' ij e and W" ij e are respectively the upper limit value of the bandwidth and the lower limit value of the bandwidth, according to the calculation formula: The analysis obtains the flow rate demand evaluation coefficient of the area numbered as j in the time period numbered as i , wherein E represents the total number of the historical preset periods, and W' represents the set bandwidth standard value; The total amount of flow usage of each region in each time period in each historical preset period is recorded as According to the calculation formula: The flow usage demand evaluation coefficient of the region numbered j in the time period numbered i is obtained by analysis Wherein Q′ ij represents the set total amount of flow usage standard value; The analysis of each traffic threshold value of each region in each time period is performed in the following manner: the total traffic usage amount of each region in each time period in each historical preset period is obtained based on the traffic usage information in the campus, the total traffic usage amount of each region in each time period in each historical preset period is subjected to normal distribution, the middle value of the normal distribution is recorded as a secondary traffic threshold value of the region in the time period, and the maximum value of the normal distribution is recorded as a primary traffic threshold value of the region in the time period, thereby obtaining the primary and secondary traffic threshold values of each region in each time period; Step two, traffic allocation: allocating traffic to each region in the current preset period according to the traffic priorities of each region in each time period, and monitoring the traffic types of each region in each time period; when the traffic threshold value is reached, the traffic of each region in each time period is subjected to speed limiting treatment based on the traffic types; The flow is allocated to each region of the current preset period according to the flow priority of each region of each time period, and the specific process is as follows: the flow consumption demand evaluation coefficient and the flow rate demand evaluation coefficient of each region of each time period are comprehensively evaluated, and the flow of each region of the current preset period is allocated according to the calculation formula: The flow comprehensive demand evaluation coefficient of the jth region is analyzed, wherein I is the total number of time periods, and the ratio of the flow comprehensive demand evaluation coefficient of each region is calculated, the flow of the current information and the network center is allocated based on the ratio of the flow comprehensive evaluation coefficient of each region, and the matching flow of each region of the current preset period is obtained. The flow demand evaluation coefficient of each region in each time period is calculated according to the following formula: The flow comprehensive demand evaluation coefficient of the jth region in the ith time period is obtained through analysis, and then the ratio of the flow comprehensive demand evaluation coefficients of each region in each time period is calculated. Based on the ratio of the flow comprehensive demand evaluation coefficients of each region in each time period, the matching flow of each region is secondarily distributed, and the matching flow of each region in each time period is obtained. Step three, traffic scheduling: when the traffic is insufficient, the traffic of each region in each time period is subjected to scheduling.

2. The campus network traffic prediction method of claim 1, wherein, The speed limiting treatment of the traffic of each region in each time period based on the traffic types is performed in the following manner: The traffic usage of each region in each time period is monitored, and the traffic usage types and total amounts of each region in each time period are obtained based on the traffic usage monitoring results; When the total traffic usage amount of each region in each time period reaches the primary traffic threshold value of the region, the traffic priority of the region in the time period is obtained based on the traffic priorities of each region in each time period, the traffic usage type of the region in the time period is obtained based on the traffic usage types of each region in each time period, the education and scientific research application characteristic traffic, the high-bandwidth application characteristic traffic and the social and tool application characteristic traffic are obtained based on the traffic usage type of the region in the time period, the education and scientific research application characteristic traffic is subjected to primary speed limiting treatment, and the high-bandwidth application characteristic traffic and the social and tool application characteristic traffic are subjected to secondary speed limiting treatment. When the traffic usage amount of a certain area in a certain period reaches the secondary traffic threshold of the area, the education and scientific research application characteristic traffic is subjected to primary speed limiting processing, the social and tool application characteristic traffic is subjected to secondary speed limiting processing, and the high bandwidth application characteristic traffic is subjected to tertiary speed limiting processing. The primary speed limiting processing is no speed limiting, the tertiary speed limiting processing is to disconnect the traffic, and the secondary speed limiting processing is to limit the speed to half of the original bandwidth.

3. The campus network traffic prediction method of claim 2, wherein, The traffic scheduling of each area in each period is specifically as follows: the total amount of traffic usage of each area in each period is obtained based on the traffic monitoring result of each area in each period in the current preset period, if the total amount of traffic usage of a certain area in a certain period reaches the matching total amount of traffic of the area in the period, the traffic priority of the area in the period and the traffic priorities of other areas in the period are obtained, then the areas with lower traffic priority than the area in the period are recorded as matching areas, the residual traffic of each matching area at the current time point is sorted in descending order, and then the area is subjected to traffic scheduling according to the sorting result, and the sorting result is updated in real time based on the scheduling result.

4. A campus network traffic prediction system that performs the campus network traffic prediction method according to any one of claims 1 to 3, characterized by, Comprise: a historical traffic analysis module for obtaining traffic usage information in the campus from the information and network center, predicting the total amount of traffic demand in the current preset period, and analyzing the traffic priority of each area in each period, and analyzing each traffic threshold of each area in each period; The traffic usage information comprises the bandwidth threshold and the total amount of traffic usage of each area in each period in each historical preset period, wherein the bandwidth threshold comprises an upper bandwidth limit value and a lower bandwidth limit value; The total amount of traffic demand in the current preset period is predicted as follows: the traffic monitoring data of each area in each period in each historical preset period is divided into a data set and a prediction set according to a preset proportion, a network traffic VMD-PSO-BiLSTM prediction model is constructed according to the data set, the prediction set is input into the network traffic VMD-PSO-BiLSTM prediction model as a data source, and the total amount of campus traffic demand in the current preset period is predicted by the network traffic VMD-PSO-BiLSTM prediction model; The analysis obtains the flow priority of each area in each time period, and the specific analysis process is as follows: based on the flow usage information in the campus, the bandwidth threshold of each area in each time period in each historical preset period is obtained, and then the flow rate demand evaluation coefficient of each area in each time period is obtained Wherein i represents the number of each time period, i is a positive integer, j represents the number of each area, and j is a positive integer; Based on the traffic usage information in the campus, the total traffic usage amount of each region in each time period in each historical preset period is obtained, and then the traffic usage demand evaluation coefficient of each region in each time period is analyzed and obtained The flow rate demand evaluation coefficient and the flow usage demand evaluation coefficient of each region in each time period are input into the flow grading model, and the flow demand characteristic value η of the region numbered j in the time period numbered i is output according to the expression of the flow grading model: The flow demand characteristic value η of the region numbered j in the time period numbered i is output according to the expression of the flow grading model: ij wherein χ' and χ'' are respectively the lower limit value and the upper limit value of the flow comprehensive demand evaluation coefficient, a region in a time period with the flow demand characteristic value of 1 is recorded as a first-level flow priority region, a region in a time period with the flow demand characteristic value of 0 is recorded as a second-level flow priority region, and a region in a time period with the flow demand characteristic value of -1 is recorded as a third-level flow priority region, and thus the first-level flow priority regions, the second-level flow priority regions and the third-level flow priority regions in each time period are obtained. The analysis obtains the flow rate demand evaluation coefficient and the flow consumption demand evaluation coefficient of each area in each time period, and the specific analysis process is as follows: the bandwidth threshold of each area in each time period in each historical preset period is denoted as W' ij e and W" ij e , wherein W' ij e and W" ij e are respectively the upper limit value of bandwidth and the lower limit value of bandwidth, according to the calculation formula: The analysis obtains the flow rate demand evaluation coefficient of the area numbered as j in the time period numbered as i , wherein E represents the total number of historical preset periods, and W' represents the set bandwidth standard value; The total flow usage amount of each region in each time period in each historical preset period is recorded as According to the calculation formula: The flow usage demand evaluation coefficient of the region numbered j in the time period numbered i is obtained by analysis Wherein Q′ ij represents the set total flow usage standard value; The analysis of each traffic threshold of each area in each period is specifically as follows: the total amount of traffic usage of each area in each period in each historical preset period is obtained based on the traffic usage information in the campus, the total amount of traffic usage of a certain area in a certain period in each historical preset period is subjected to normal distribution, the middle value of the normal distribution is recorded as the secondary traffic threshold of the area in the period, and the maximum value of the normal distribution is recorded as the primary traffic threshold of the area in the period, thereby obtaining the primary traffic threshold and the secondary traffic threshold of each area in each period; a traffic allocation module for allocating traffic to each area in the current preset period according to the traffic priority of each area in each period, and monitoring the traffic type of each area in each period, and limiting the traffic of each area in each period based on the traffic type when the traffic threshold is reached. The flow is allocated to each region of the current preset period according to the flow priority of each region of each time period, and the specific process is as follows: the flow consumption demand evaluation coefficient and the flow rate demand evaluation coefficient of each region of each time period are comprehensively evaluated, and the flow of each region of the current preset period is allocated according to the calculation formula: The flow comprehensive demand evaluation coefficient of the jth region is analyzed, wherein I is the total number of time periods, and the ratio of the flow comprehensive demand evaluation coefficient of each region is calculated, the flow of the current information and the network center is allocated based on the ratio of the flow comprehensive evaluation coefficient of each region, and the matching flow of each region of the current preset period is obtained. The flow demand evaluation coefficient of each region in each time period is calculated according to the following formula: The flow comprehensive demand evaluation coefficient of the jth region in the ith time period is obtained through analysis, and then the ratio of the flow comprehensive demand evaluation coefficients of each region in each time period is calculated. Based on the ratio of the flow comprehensive demand evaluation coefficients of each region in each time period, the matching flow of each region is secondarily distributed, and the matching flow of each region in each time period is obtained. Traffic scheduling module: for when the traffic is insufficient, the traffic of each region in each time period is scheduled.

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