Bandwidth scheduling method and system for high-speed routing switching

Abstract

The present invention relates to the technical field of high-speed routing, and provides a bandwidth scheduling method and system for high-speed routing switching, including allocating each port of a high-speed routing switching device according to network traffic, and analyzing the initial bandwidth value of each port based on the allocation result; using a bandwidth monitoring module to monitor the real-time bandwidth usage of each port of the high-speed routing switching device to obtain a bandwidth allocation result; generating a traffic scheduling strategy based on the bandwidth allocation result, inputting the traffic scheduling strategy into the traffic scheduling module for configuration, comparing the traffic scheduling strategy with the real-time bandwidth usage monitored by the bandwidth monitoring module, obtaining the bandwidth scheduling comparison result and inputting it into the bandwidth scheduling optimization module for bandwidth scheduling optimization. By dynamically configuring the traffic scheduling strategy, efficient utilization of bandwidth resources and optimized management of network traffic are achieved, and the problem of insufficient flexibility such as low bandwidth utilization and resource waste when the network traffic fluctuates greatly is improved.

Description

Technical Field

[0001] The present application relates to the technical field of high-speed routing, and in particular to a bandwidth scheduling method and system for high-speed routing switching. Background Art

[0002] With the rapid development of the Internet and the continuous increase in data traffic, high-speed routing and switching equipment has become increasingly important in network communications. These devices not only need to process massive amounts of data packets, but also need to achieve efficient bandwidth management to ensure the smooth operation and efficient use of the network.

[0003] In the related technical means, bandwidth scheduling methods are mainly based on preset fixed bandwidth allocation strategies. These methods usually implement basic traffic management and control by allocating fixed bandwidth values ​​to each port, thus ensuring the fairness and stability of bandwidth allocation to a certain extent.

[0004] Regarding the above technical solutions, although basic network bandwidth management can be achieved through a fixed bandwidth allocation strategy, when network traffic fluctuates greatly, there are problems of insufficient flexibility such as low bandwidth utilization and resource waste. Summary of the invention

[0005] In order to improve the problem of insufficient flexibility such as low bandwidth utilization and resource waste when network traffic fluctuates greatly, the present application provides a bandwidth scheduling method and system for high-speed routing switching, which can make real-time adjustments according to actual network traffic conditions, thereby improving bandwidth utilization and reducing resource waste.

[0006] The present invention provides a bandwidth scheduling method for high-speed routing switching, which is applied to high-speed routing switching equipment. The high-speed routing switching equipment includes a bandwidth monitoring module, a traffic scheduling module, a bandwidth allocation module and a bandwidth scheduling optimization module. The bandwidth scheduling method includes: allocating bandwidth to each port of the high-speed routing switching equipment according to network traffic, and analyzing the initial bandwidth value of each port based on the allocation result; using the bandwidth monitoring module to monitor the real-time bandwidth usage of each port of the high-speed routing switching equipment to obtain the bandwidth usage rate of each port; inputting all the bandwidth usage rates and all the initial bandwidth values ​​into a preset scheduling algorithm model to obtain a bandwidth adjustment plan, and adjusting the bandwidth usage of the high-speed routing switching equipment based on the bandwidth adjustment plan. The bandwidth of each port of the switching device is adjusted and monitored to obtain an adjusted bandwidth usage rate; the bandwidth adjustment plan is dynamically optimized based on the adjusted bandwidth usage rate, and a bandwidth allocation plan is generated based on the optimization result; the bandwidth allocation plan is input into the bandwidth allocation module to re-allocate bandwidth to each port of the high-speed routing switching device to obtain a bandwidth allocation result; a traffic scheduling strategy is generated based on the bandwidth allocation result, the traffic scheduling strategy is input into the traffic scheduling module for configuration, the traffic scheduling strategy is compared with the real-time bandwidth usage monitored by the bandwidth monitoring module to obtain a bandwidth scheduling comparison result, and the bandwidth scheduling comparison result is input into the bandwidth scheduling optimization module for bandwidth scheduling optimization.

[0007] As a preferred solution, the steps of allocating bandwidth to each port of the high-speed routing switching device according to network traffic and analyzing the initial bandwidth value of each port based on the allocation result include: collecting network traffic through a network traffic monitor, classifying the network traffic using a clustering algorithm to obtain each category of traffic; determining the bandwidth priority of each port according to the demand of each port of the high-speed routing switching device for each category of traffic; allocating bandwidth to the bandwidth priority by a proportional allocation method to obtain an allocation result, and performing statistical analysis on the allocation result using a statistical analysis tool to obtain the initial bandwidth value of each port.

[0008] As a preferred solution, the step of using the bandwidth monitoring module to monitor the real-time bandwidth usage of each port of the high-speed routing switching device to obtain the bandwidth usage rate of each port includes: collecting the real-time data stream of each port of the high-speed routing switching device through a data packet analysis tool to obtain the original bandwidth data of each port; using data cleaning technology to pre-process the original bandwidth data of each port to obtain processed bandwidth data of each port, and inputting the processed bandwidth data of each port into a preset calculation formula to calculate the bandwidth usage rate of each port. The preset calculation formula is as follows: Bandwidth usage rate = (processed bandwidth data / maximum available bandwidth) × 100%.

[0009] As a preferred solution, the steps of inputting all the bandwidth utilization rates and all the initial bandwidth values ​​into a preset scheduling algorithm model to obtain a bandwidth adjustment plan, adjusting and monitoring the bandwidth of each port of the high-speed routing switching device based on the bandwidth adjustment plan, and obtaining the adjusted bandwidth utilization rate include: sorting and analyzing all the bandwidth utilization rates through statistical tools to obtain traffic distribution characteristics, congestion hotspot characteristics and traffic stability, analyzing the traffic distribution characteristics using principal component analysis to obtain traffic peaks and traffic troughs, applying time series analysis to process the congestion hotspot characteristics based on the traffic peak to obtain congestion frequency, correlating the traffic trough with the traffic stability through the correlation coefficient method to obtain a stability index; performing collaborative optimization processing on the congestion frequency and the stability index based on a preset linear programming model to generate a preliminary scheduling plan; arranging and grouping all the initial bandwidth values ​​using bubble sort to obtain a high-demand bandwidth group and a low-demand bandwidth group, and adjusting the weight of the high-demand bandwidth group through the weighted sum method to obtain a priority adjustment bandwidth, The low-demand bandwidth group is processed by K-means clustering to obtain a stable allocated bandwidth; the priority adjustment bandwidth and the stable allocated bandwidth are comprehensively evaluated and processed, and a comprehensive bandwidth plan is generated based on the evaluation result, and the preliminary scheduling plan and the comprehensive bandwidth plan are processed by a greedy algorithm to obtain a bandwidth adjustment plan; the bandwidth adjustment plan is decomposed by partial least squares method, and key parameters, secondary parameters and auxiliary parameters are generated based on the decomposition result, and the key parameters are adjusted twice by using a preset optimization rule to form a first scheduling parameter and a second scheduling parameter; the first scheduling parameter and the secondary parameter are matched and optimized according to the function optimal solution method, and an adjustment index is generated based on the optimization result, and the distance between the second scheduling parameter and the auxiliary parameter is optimized by using Manhattan distance, and an adjustment vector is generated based on the optimization result; the adjustment index and the adjustment vector are combined and calculated by a constraint optimization method to obtain a bandwidth optimization matrix, and the bandwidth optimization matrix is ​​used to adjust the bandwidth of each port of the high-speed routing switching device, and the adjusted bandwidth utilization rate is calculated based on the adjustment result.

[0010] As a preferred solution, the step of dynamically optimizing the bandwidth adjustment scheme based on the adjusted bandwidth usage rate and generating a bandwidth allocation scheme based on the optimization result includes: analyzing the adjusted bandwidth usage rate based on statistical software to obtain a bandwidth usage rate analysis result; iteratively optimizing the bandwidth adjustment scheme based on the bandwidth usage rate analysis result by a particle swarm optimization algorithm to obtain an iterative bandwidth adjustment scheme; optimizing the iterative bandwidth adjustment scheme by a dynamic adjustment strategy to obtain an optimization result, and smoothing the optimization result by a Kalman filter to obtain a bandwidth allocation scheme.

[0011] As a preferred solution, the step of inputting the bandwidth allocation scheme into the bandwidth allocation module to re-allocate bandwidth to each port of the high-speed routing switching device to obtain a bandwidth allocation result includes: using the shortest path algorithm to perform path optimization analysis on the bandwidth allocation scheme, and generating optimized allocation path information based on the analysis result, inputting the optimized allocation path information into the bandwidth allocation module, and in the bandwidth allocation module, allocating and executing the optimized allocation path information through a control instruction algorithm to obtain a first allocation result; using a network performance monitoring tool to monitor and analyze the bandwidth usage of the bandwidth allocation scheme and the bandwidth usage of the first allocation result to obtain first monitoring analysis data and second monitoring analysis data; comparing the first monitoring analysis data with the second monitoring analysis data to generate a comparison analysis result; and using a proportional-integral-differential control algorithm to adjust the bandwidth allocation scheme based on the comparison analysis result to obtain a bandwidth allocation result.

[0012] As a preferred solution, the steps of generating a traffic scheduling strategy based on the bandwidth allocation result, inputting the traffic scheduling strategy into the traffic scheduling module for configuration, comparing the traffic scheduling strategy with the real-time bandwidth usage monitored by the bandwidth monitoring module to obtain a bandwidth scheduling comparison result, and inputting the bandwidth scheduling comparison result into the bandwidth scheduling optimization module for bandwidth scheduling optimization include: classifying the bandwidth allocation result by a support vector machine, generating feature set data and behavior pattern data based on the classification result, grading the feature set data by using a hierarchical analysis method to generate a preliminary feature classification and a secondary feature classification; cross-validating the behavior pattern data by using the preliminary feature classification based on a cross-validation method to generate a verification result, performing aggregation analysis on the verification result and the secondary feature classification by using a data fusion algorithm to obtain a stability index; stratifying the stability index by using hierarchical clustering to obtain a grading index and a stability strategy, and performing a classification analysis on the stability index by using a model. Fuzzy logic is used to optimize the parameters of the grading indicators to obtain a basic scheduling strategy; the basic scheduling strategy is weightedly evaluated according to the entropy weight method, strategy segmentation and strategy integration are generated based on the evaluation results, the strategy segmentation is encoded through hash mapping to obtain a strategy matrix, and the strategy integration is structurally optimized using a Block chain structure to obtain an integrated decision table; the strategy matrix, the integrated decision table and the stability strategy are input into a preset deep neural network model, and in the deep neural network model, the stability strategy is tuned based on the strategy matrix and the integrated decision table using a convolution operation to obtain a traffic scheduling strategy; the traffic scheduling strategy is reliability tested through Monte Carlo simulation to obtain a test analysis result; the test analysis result is compared with the real-time bandwidth usage monitored by the bandwidth monitoring module to obtain a comparison analysis result; the comparison analysis result is used as real-time feedback information and input into the bandwidth scheduling optimization module for real-time bandwidth scheduling optimization processing.

[0013] The present application also provides a bandwidth scheduling system for high-speed routing switching, which is applied to high-speed routing switching equipment. The high-speed routing switching equipment includes a bandwidth monitoring module, a traffic scheduling module, a bandwidth allocation module and a bandwidth scheduling optimization module, and is characterized in that the bandwidth scheduling system includes: an analysis unit, which is used to allocate bandwidth to each port of the high-speed routing switching equipment according to network traffic, and analyze the initial bandwidth value of each port based on the allocation result; a monitoring unit, which is used to use the bandwidth monitoring module to monitor the real-time bandwidth usage of each port of the high-speed routing switching equipment to obtain the bandwidth usage rate of each port; an adjustment unit, which is used to input all the bandwidth usage rates and all the initial bandwidth values ​​into a preset scheduling algorithm model to obtain a bandwidth adjustment plan, and adjust the bandwidth of the high-speed routing switching equipment based on the bandwidth adjustment plan. The invention relates to a method for adjusting and monitoring the bandwidth of each port of the high-speed routing switching device to obtain an adjusted bandwidth usage rate; an optimization unit, which is used to dynamically optimize the bandwidth adjustment plan based on the adjusted bandwidth usage rate, and generate a bandwidth allocation plan based on the optimization result; an allocation unit, which is used to input the bandwidth allocation plan into the bandwidth allocation module to re-allocate bandwidth to each port of the high-speed routing switching device to obtain a bandwidth allocation result; a scheduling unit, which is used to generate a traffic scheduling strategy based on the bandwidth allocation result, input the traffic scheduling strategy into the traffic scheduling module for configuration, compare the traffic scheduling strategy with the real-time bandwidth usage monitored by the bandwidth monitoring module to obtain a bandwidth scheduling comparison result, and input the bandwidth scheduling comparison result into the bandwidth scheduling optimization module for bandwidth scheduling optimization.

[0014] Compared with the prior art, the present application has the following beneficial effects: high bandwidth utilization and sufficient flexibility. By using the bandwidth monitoring module to monitor the bandwidth usage of each port in real time, and combining with the preset scheduling algorithm model, and then by allocating the initial bandwidth value, monitoring the bandwidth utilization rate in real time, inputting the scheduling algorithm model for adjustment, dynamically optimizing the bandwidth adjustment plan, generating the bandwidth allocation plan, and configuring the traffic scheduling strategy, the efficient utilization of bandwidth resources and the optimized management of network traffic are achieved, and the bandwidth allocation can be flexibly adjusted in the case of large fluctuations in network traffic to avoid resource waste and network congestion, thereby improving the stability and transmission efficiency of the entire network, so that high-speed routing switching equipment can maintain an efficient and stable operating state in various complex network environments, and improve the problems of insufficient flexibility such as low bandwidth utilization and resource waste when the network traffic fluctuates greatly. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0016] The structures, proportions, sizes, etc. illustrated in the drawings of this specification are only used to match the contents disclosed in the specification so as to facilitate understanding and reading by persons familiar with this technology. They are not used to limit the conditions under which the present invention can be implemented, and therefore have no substantive technical significance. Any structural modification, change in proportion or adjustment of size, without affecting the effects and purposes that can be achieved by the present invention, should still fall within the scope of the technical contents disclosed by the present invention.

[0017] Figure 1 It is a flow chart of a bandwidth scheduling method for high-speed routing switching provided by an embodiment of the present invention;

[0018] Figure 2 The present invention is a schematic block diagram of the structure of a bandwidth scheduling system for high-speed routing switching provided by an embodiment of the present invention.

[0019] Description of reference numerals:

[0020] 10. Bandwidth scheduling system for high-speed routing switching; 11. Analysis unit; 12. Monitoring unit; 13. Adjustment unit; 14. Optimization unit; 15. Allocation unit; 16. Scheduling unit. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.

[0023] It should also be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0024] It should be further understood that the term “and / or” used in the specification and appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0025] The technical solution of the present invention is further described below with reference to the accompanying drawings and through specific implementation methods. Example

[0026] like Figure 1 As shown, a bandwidth scheduling method for high-speed routing switching provided in an embodiment of the present application is applied to a high-speed routing switching device. The high-speed routing switching device includes a bandwidth monitoring module, a traffic scheduling module, a bandwidth allocation module, and a bandwidth scheduling optimization module. The bandwidth scheduling method includes steps S100 to S600.

[0027] Step S100: Allocate bandwidth to each port of the high-speed routing switch device according to network traffic, and analyze the initial bandwidth value of each port based on the allocation result.

[0028] The bandwidth monitoring module is used to collect network traffic data, analyze the traffic characteristics and requirements of each port, and use the bandwidth allocation algorithm to determine the initial bandwidth value of each port. Specifically, bandwidth is allocated to each port based on the peak, average and fluctuation of the traffic, combined with historical traffic data and current network status to ensure that the bandwidth utilization of each port is optimal.

[0029] For example, a higher initial bandwidth value is allocated to certain high-traffic ports, such as core switching ports, to meet high data transmission requirements; whereas a lower initial bandwidth value is allocated to low-traffic ports, such as peripheral access ports.

[0030] Step S200: Use a bandwidth monitoring module to monitor the real-time bandwidth usage of each port of the high-speed routing switch device to obtain the bandwidth usage rate of each port.

[0031] In this step, the bandwidth monitoring module collects the flow data of each port in real time and calculates the bandwidth utilization rate. Specifically, by monitoring the number and size of data packets flowing in and out of the port, combined with the time window, the real-time bandwidth utilization rate of each port is calculated, and the monitoring data is recorded for subsequent analysis and adjustment.

[0032] For example, data is collected every few seconds, recorded and processed on the background server, and the bandwidth usage information of each port is updated in real time.

[0033] Step S300: input all bandwidth utilization rates and all initial bandwidth values ​​into a preset scheduling algorithm model to obtain a bandwidth adjustment plan, adjust and monitor the bandwidth of each port of the high-speed routing switching device based on the bandwidth adjustment plan, and obtain the adjusted bandwidth utilization rate.

[0034] In this step, the scheduling algorithm model calculates the optimized bandwidth adjustment plan based on the input bandwidth utilization and initial bandwidth value; specifically, considering the current network status and traffic trend, the algorithm model is iterated multiple times to determine the optimal bandwidth adjustment plan and adjust the bandwidth of each port.

[0035] For example, if the bandwidth usage of a port is high for a long time, while the bandwidth usage of other ports is low, part of the bandwidth will be reallocated to the port with high usage to balance the overall network load.

[0036] Step S400: dynamically optimize the bandwidth adjustment scheme based on the adjusted bandwidth usage rate, and generate a bandwidth allocation scheme based on the optimization result.

[0037] In this step, the bandwidth adjustment scheme is re-optimized after obtaining new usage data; specifically, the bandwidth allocation of each port is updated in real time through a dynamic adjustment model to ensure optimal allocation of bandwidth resources in the entire network.

[0038] For example, when burst traffic occurs on certain ports, their bandwidth allocation is adjusted immediately to avoid network congestion and data transmission delays.

[0039] Step S500: Input the bandwidth allocation scheme into the bandwidth allocation module to re-allocate bandwidth to each port of the high-speed routing switch device to obtain a bandwidth allocation result.

[0040] In this step, the bandwidth allocation module reallocates the bandwidth of each port according to the latest bandwidth allocation plan; specifically, the bandwidth adjustment information is sent to each port to ensure that each port uses the bandwidth according to the new plan.

[0041] For example, a bandwidth configuration command is sent through a control interface so that the actual bandwidth setting of each port is consistent with the allocation scheme.

[0042] Step S600: Generate a traffic scheduling strategy based on the bandwidth allocation result, input the traffic scheduling strategy into the traffic scheduling module for configuration, compare the traffic scheduling strategy with the real-time bandwidth usage monitored by the bandwidth monitoring module to obtain a bandwidth scheduling comparison result, and input the bandwidth scheduling comparison result into the bandwidth scheduling optimization module for bandwidth scheduling optimization.

[0043] In this step, the bandwidth allocation result generates a traffic scheduling strategy, which is configured through the traffic scheduling module and compared with the real-time monitoring data; specifically, the traffic scheduling strategy is applied to high-speed routing switching equipment to dynamically adjust the traffic path and priority to achieve optimal traffic management.

[0044] For example, different priorities and paths can be set for different types of traffic (such as video streaming, web browsing, file transfer, etc.) to ensure the stable transmission of critical business traffic.

[0045] In this embodiment, bandwidth is allocated to each port of a high-speed routing switching device through network traffic, and the initial bandwidth value of each port is analyzed based on the allocation result. Then, the bandwidth monitoring module is used to monitor the real-time bandwidth usage of each port to obtain the bandwidth utilization rate of each port. Next, all bandwidth utilization rates and all initial bandwidth values ​​are input into a preset scheduling algorithm model to generate a bandwidth adjustment scheme, and bandwidth adjustment and monitoring are performed on each port based on this scheme to obtain the adjusted bandwidth utilization rate. Subsequently, the bandwidth adjustment scheme is dynamically optimized based on the adjusted bandwidth utilization rate, and a bandwidth allocation scheme is generated. Finally, the bandwidth allocation scheme is input into the bandwidth allocation module to allocate bandwidth to each port again, and a traffic scheduling strategy is generated based on the bandwidth allocation result, configured through the traffic scheduling module, and compared with the real-time bandwidth usage to obtain the bandwidth scheduling comparison result, and the result is input into the bandwidth scheduling optimization module for optimization. By dynamically monitoring and adjusting bandwidth allocation in real time, not only the bandwidth utilization rate is improved, but also the waste of resources is reduced. By using a preset scheduling algorithm model to generate and optimize the bandwidth adjustment scheme, the flexibility and efficiency of bandwidth allocation are ensured. In addition, real-time optimization and dynamic adjustment based on actual network traffic conditions improve the stability and reliability of the network, making high-speed routing and switching equipment perform better when dealing with network traffic fluctuations, and improving the lack of flexibility such as low bandwidth utilization and resource waste when network traffic fluctuates greatly. Example

[0046] In step S100, network traffic is collected by a network traffic monitor, and the network traffic is classified using a clustering algorithm to obtain traffic of each category.

[0047] The network traffic data is collected in real time through the network traffic monitor, and the clustering algorithm is used to process and classify the data to obtain different types of traffic. Specifically, the K-means clustering algorithm is used to perform cluster analysis on the traffic according to the characteristic values ​​of the traffic (such as source address, destination address, protocol type, packet size, etc.), and different types of traffic are divided, such as video traffic, web browsing traffic, file transfer traffic, etc.

[0048] For example, during network monitoring, a large amount of video traffic data is found within a certain period of time. After cluster analysis, it is classified as video traffic, which facilitates subsequent bandwidth priority setting and management.

[0049] The bandwidth priority of each port is determined based on the demand of each port of the high-speed routing switching device for each type of traffic.

[0050] By analyzing the demand for different types of traffic at each port of high-speed routing and switching equipment, the bandwidth priority of each port is determined. Specifically, based on the historical traffic data and current traffic characteristics of each port, combined with business needs, the AHP (analytic hierarchy process) is used to evaluate the importance of different types of traffic and determine the bandwidth priority of each port to ensure that critical business traffic can obtain bandwidth resources first.

[0051] For example, for core switching ports, they mainly handle large amounts of data transmission and high-priority business traffic, so they are set to high bandwidth priority; while for some peripheral access ports, their traffic requirements are low, so they are set to low bandwidth priority.

[0052] The bandwidth is allocated to the bandwidth priority by using a proportional allocation method to obtain an allocation result, and the allocation result is statistically analyzed by using a statistical analysis tool to obtain an initial bandwidth value of each port.

[0053] By allocating bandwidth according to the bandwidth priority of each port, the total bandwidth resources are allocated to each port in proportion using the proportional allocation method; specifically, according to the bandwidth priority of each port and the total bandwidth resources, the bandwidth value to be allocated to each port is calculated to ensure the reasonable allocation of bandwidth resources. Then, the allocation results are analyzed using statistical analysis tools to confirm the initial bandwidth value of each port, and these data are recorded and stored for subsequent use.

[0054] For example, if the total bandwidth resource is 1000Mbps, according to the bandwidth priority and proportional allocation method of each port, the core switching port will be allocated 400Mbps, while the peripheral access port will be allocated 100Mbps.

[0055] In step S200, the real-time data stream of each port of the high-speed routing switch device is collected by a data packet analysis tool to obtain the original bandwidth data of each port.

[0056] The real-time data stream of each port is collected and recorded through the data packet analysis tool to obtain the original bandwidth data of each port; specifically, the data packets of each port are captured using a packet capture tool (such as Wireshark), and the size, transmission time and other information of each data packet are recorded to obtain the original bandwidth data.

[0057] For example, during the monitoring process, data is captured from all ports every few seconds, and the amount of data transmitted by each port during this period is recorded, thereby obtaining the original bandwidth data of each port.

[0058] The original bandwidth data of each port is preprocessed using data cleaning technology to obtain the processed bandwidth data of each port. The processed bandwidth data of each port is input into a preset calculation formula to calculate the bandwidth utilization rate of each port. The preset calculation formula is as follows: Bandwidth utilization rate = (processed bandwidth data / maximum available bandwidth) × 100%.

[0059] The collected raw bandwidth data is preprocessed through data cleaning technology, including steps such as removing noise data, filling missing data and data normalization, to obtain the processed bandwidth data of each port; specifically, the data cleaning script written in Python is used to process the captured packet data one by one, remove abnormal data and invalid data, and convert the data format. Then, the processed bandwidth data is substituted into the preset calculation formula to calculate the bandwidth utilization rate of each port.

[0060] For example, if the maximum available bandwidth of a port is 500Mbps and the preprocessed bandwidth data is 250Mbps over a period of time, the bandwidth utilization rate is calculated as follows: Bandwidth utilization rate = (250Mbps / 500Mbps) × 100% = 50%.

[0061] In step S300, all bandwidth utilization rates are sorted and analyzed by statistical tools to obtain traffic distribution characteristics, congestion hotspot characteristics and traffic stability. The traffic distribution characteristics are analyzed using principal component analysis to obtain traffic peaks and traffic troughs. Time series analysis is used to process the congestion hotspot characteristics based on traffic peaks to obtain congestion frequencies. The traffic troughs are correlated with traffic stability through the correlation coefficient method to obtain stability indicators.

[0062] The bandwidth utilization data of all ports are collated and analyzed through statistical tools to extract traffic distribution characteristics, congestion hotspot characteristics and stability indicators. Specifically, the principal component analysis (PCA) method is used to reduce the dimension of bandwidth utilization data, identify the main traffic characteristics, and determine the peak and trough periods of traffic. Then, the time series analysis method is applied to analyze the congestion hotspot characteristics during the peak traffic period and calculate the congestion frequency. At the same time, the correlation coefficient method is used to correlate the traffic trough with traffic stability to obtain the stability indicator.

[0063] For example, PCA analysis shows that the traffic peak period for a certain port is from 10:00 to 12:00 every day, and the congestion hotspots are mainly concentrated in the core switching port, while the traffic trough period is from 2:00 to 4:00 in the morning, during which the traffic is stable.

[0064] Based on the preset linear programming model, the congestion frequency and stability indicators are collaboratively optimized to generate a preliminary scheduling plan.

[0065] Through the preset linear programming model, the congestion frequency and smoothness indicators of the traffic are collaboratively optimized; specifically, a multi-objective linear programming model is constructed, and the congestion frequency and traffic smoothness are taken as optimization objectives. The constraints and objective functions are solved to generate a preliminary traffic scheduling plan.

[0066] For example, the objective function is set in the model to minimize the congestion frequency and maximize the flow smoothness. Through the optimization algorithm, a preliminary scheduling plan is obtained, which can effectively reduce congestion during peak traffic periods and maintain flow stability during low traffic periods.

[0067] Bubble sort is used to arrange and group all the initial bandwidth values ​​to obtain a high-demand bandwidth group and a low-demand bandwidth group. The weight of the high-demand bandwidth group is adjusted by weighted summation method to obtain priority adjustment bandwidth. The low-demand bandwidth group is processed by K-means clustering to obtain stable allocation of bandwidth.

[0068] The initial bandwidth values ​​of all ports are sorted by the bubble sort algorithm, and grouped according to the sorting results into high-demand bandwidth group and low-demand bandwidth group; specifically, the weighted summation method is used for the high-demand bandwidth group to adjust its weight according to the actual demand and importance of each port to obtain the priority adjustment bandwidth. At the same time, the K-means clustering algorithm is used to perform cluster analysis on the low-demand bandwidth group to determine the stable allocation bandwidth of each port.

[0069] For example, some core ports are determined as high-demand bandwidth groups through bubble sorting and are assigned higher weights, while peripheral access ports are classified as low-demand bandwidth groups and their stable allocated bandwidths are determined after K-means clustering.

[0070] The priority adjustment bandwidth and the stable allocation bandwidth are comprehensively evaluated and processed, and a comprehensive bandwidth plan is generated based on the evaluation results. The preliminary scheduling plan and the comprehensive bandwidth plan are processed using a greedy algorithm to obtain a bandwidth adjustment plan.

[0071] By comprehensively evaluating the priority adjustment of bandwidth and the stable allocation of bandwidth, specifically, a multi-objective evaluation method is adopted to compare the bandwidth requirements of each port with the actual traffic, and evaluate the bandwidth utilization efficiency of each port; then, the greedy algorithm is used to optimize the preliminary scheduling plan and the comprehensive bandwidth plan to ensure the optimal allocation of bandwidth resources.

[0072] For example, for a port in the high-demand bandwidth group, if its bandwidth utilization is high and its importance is high, its bandwidth demand is preferentially met in the greedy algorithm, while the ports in the low-demand bandwidth group are appropriately adjusted to ensure the optimal allocation of overall bandwidth resources.

[0073] The bandwidth adjustment scheme is decomposed by partial least squares method, and key parameters, secondary parameters and auxiliary parameters are generated based on the decomposition results. The key parameters are adjusted twice by using preset optimization rules to form first scheduling parameters and second scheduling parameters.

[0074] The bandwidth adjustment scheme is decomposed by partial least squares method. Specifically, the key parameters, secondary parameters and auxiliary parameters in the bandwidth adjustment scheme are extracted and analyzed and processed respectively. The key parameters are adjusted twice by using preset optimization rules to ensure that the most important parameters are optimized, and the first scheduling parameters and the second scheduling parameters are generated to facilitate effective scheduling in practical applications.

[0075] For example, when adjusting the bandwidth of a core port, the key parameters are its maximum bandwidth value and current usage rate, the secondary parameter is its historical bandwidth usage, and the auxiliary parameter is the specific type and number of devices connected to it. By analyzing and optimizing these parameters, reasonable scheduling parameters are generated.

[0076] According to the function optimal solution method, the first scheduling parameter and the secondary parameter are matched and optimized, and an adjustment index is generated based on the optimization result. The second scheduling parameter and the auxiliary parameter are distance optimized using Manhattan distance, and an adjustment vector is generated based on the optimization result.

[0077] The first scheduling parameter and the secondary parameter are matched and optimized through the function optimal solution method. Specifically, by solving the optimization model, the best matching relationship between the parameters is obtained, and the optimized adjustment index is generated. Then, the Manhattan distance is used to optimize the distance between the second scheduling parameter and the auxiliary parameter, the optimal distance between each parameter is calculated, and the adjustment vector is generated to ensure the overall optimization effect of the bandwidth adjustment scheme.

[0078] For example, if the first scheduling parameter of a port is bandwidth utilization rate and the secondary parameter is bandwidth utilization efficiency, the best matching relationship between the two is determined through the function optimal solution method to obtain the optimized bandwidth adjustment index; then the auxiliary parameters are optimized through the Manhattan distance to generate the final adjustment vector.

[0079] The adjustment index and the adjustment vector are combined and calculated by the constraint optimization method to obtain a bandwidth optimization matrix. The bandwidth optimization matrix is ​​used to adjust the bandwidth of each port of the high-speed routing switching device, and the adjusted bandwidth utilization rate is calculated based on the adjustment result.

[0080] The adjustment index and adjustment vector are combined and calculated by the constraint optimization method. Specifically, all the adjustment indexes and adjustment vectors are input into the optimization model and solved to obtain the bandwidth optimization matrix. The bandwidth optimization matrix is ​​used to adjust the bandwidth of each port to ensure that the bandwidth allocation of each port meets the optimization target. Then, the bandwidth adjustment effect is evaluated and recorded according to the adjusted bandwidth utilization rate to ensure the optimal allocation and use of bandwidth resources.

[0081] For example, the bandwidth optimization matrix can be used to adjust a core port and optimize its bandwidth utilization from 70% to 85%. By properly allocating bandwidth to other ports, the overall network bandwidth utilization can be improved.

[0082] In step S400, the adjusted bandwidth usage is analyzed based on statistical software to obtain a bandwidth usage analysis result.

[0083] The adjusted bandwidth utilization data of each port is analyzed through statistical software. Specifically, statistical analysis methods are used to conduct in-depth analysis of bandwidth usage, identify the main characteristics and trends of bandwidth utilization, and generate a detailed bandwidth utilization analysis report.

[0084] For example, by analyzing the adjusted bandwidth utilization data of a certain port, it was found that its bandwidth utilization during peak hours increased significantly and the overall network bandwidth utilization increased by 15%.

[0085] The bandwidth adjustment scheme is iteratively optimized based on the bandwidth utilization analysis results through the particle swarm optimization algorithm to obtain the iterative bandwidth adjustment scheme.

[0086] The bandwidth adjustment scheme is further optimized through the particle swarm optimization algorithm. Specifically, based on the results of bandwidth utilization analysis, the bandwidth allocation strategy of each port is iteratively updated to ensure the optimal utilization of bandwidth resources. Through multiple iterations, the bandwidth adjustment scheme that optimizes network performance is found.

[0087] For example, after several iterations of optimization, the initial bandwidth adjustment scheme has achieved a reasonable bandwidth utilization rate for each port, and the bandwidth utilization efficiency of the entire network has been significantly improved.

[0088] The dynamic adjustment strategy is used to optimize the iterative bandwidth adjustment scheme to obtain the optimization result, and the optimization result is smoothed by Kalman filtering to obtain the bandwidth allocation scheme.

[0089] The iteratively optimized bandwidth adjustment scheme is optimized through dynamic adjustment strategies. Specifically, the bandwidth allocation strategy of each port is dynamically adjusted according to the real-time network traffic changes. The Kalman filtering method is used to smooth the optimization results, eliminate data fluctuations and noise, and generate a stable bandwidth allocation scheme.

[0090] For example, during the optimization process, whenever a significant change in network traffic is detected, bandwidth allocation is dynamically adjusted to ensure that the bandwidth utilization of each port remains optimal.

[0091] In step S500, the shortest path algorithm is used to perform path optimization analysis on the bandwidth allocation plan, and based on the analysis results, optimized allocation path information is generated, and the optimized allocation path information is input into the bandwidth allocation module. In the bandwidth allocation module, the optimized allocation path information is allocated and executed through the control instruction algorithm to obtain the first allocation result.

[0092] The bandwidth allocation scheme is analyzed for path optimization through the shortest path algorithm. Specifically, the shortest data transmission path from each port to the destination is determined to ensure the efficiency and reliability of data transmission. The optimized allocation path information is input into the bandwidth allocation module, and the bandwidth of each port is accurately configured and allocated through the control instruction algorithm to generate the first allocation result.

[0093] For example, the shortest path algorithm is used to determine the data transmission path from the core switching port to each access port, and based on the optimization result, the bandwidth of the core switching port is preferentially allocated to meet the data transmission demand.

[0094] The network performance monitoring tool is used to monitor and analyze the bandwidth usage of the bandwidth allocation scheme and the bandwidth usage of the first allocation result to obtain first monitoring and analysis data and second monitoring and analysis data.

[0095] The implemented bandwidth allocation plan is monitored and analyzed in real time through the network performance monitoring tool. Specifically, the bandwidth usage of each port after the bandwidth allocation is executed is recorded to generate the first monitoring and analysis data; then, the first allocation result is compared and analyzed to generate the second monitoring and analysis data to ensure the effectiveness and rationality of the bandwidth allocation.

[0096] For example, the monitoring tool records bandwidth usage on a port within 30 minutes after bandwidth allocation is performed, finds that bandwidth utilization increases from 60% to 80%, and generates a monitoring analysis report.

[0097] The first monitoring and analysis data is compared with the second monitoring and analysis data to generate a comparison and analysis result.

[0098] By comparing the first monitoring and analysis data with the second monitoring and analysis data, specifically, using a comparative analysis method, a comprehensive comparison is performed on the two data sets, the actual effect and optimization direction of the bandwidth allocation solution are evaluated, and a comparative analysis result is generated.

[0099] For example, through comparative analysis, it was found that the bandwidth utilization of some ports changed significantly before and after optimization, providing a reference for further adjustments.

[0100] The proportional-integral-derivative control algorithm is used to adjust the bandwidth allocation scheme based on the comparison and analysis results to obtain the bandwidth allocation result.

[0101] The bandwidth allocation scheme is adjusted through the proportional-integral-differential control algorithm. Specifically, according to the comparison and analysis results, the bandwidth allocation strategy of each port is dynamically adjusted to optimize the utilization of bandwidth resources and generate the final bandwidth allocation result.

[0102] For example, through the PID control algorithm, the bandwidth allocation strategy of a port can be adjusted in real time to ensure that its bandwidth utilization rate during peak hours remains at around 90%.

[0103] In step S600, the bandwidth allocation result is classified by a support vector machine, and feature set data and behavior pattern data are generated based on the classification result. The feature set data is classified by using a hierarchical analysis method to generate a preliminary feature classification and a secondary feature classification.

[0104] The bandwidth allocation results are classified and processed through support vector machine. Specifically, the bandwidth allocation results are input into the support vector machine model for data classification to generate feature set data and behavior pattern data. The data are graded using hierarchical analysis method to ensure the accuracy and scientificity of data analysis and generate preliminary feature classification and secondary feature classification.

[0105] For example, after the support vector machine classifies the bandwidth allocation results, it generates a feature set containing the bandwidth usage characteristics of each port, and the behavior pattern data contains the bandwidth usage pattern of each port. After the data are classified using the hierarchical analysis method, the preliminary feature classification and secondary feature classification are generated for subsequent optimization processing.

[0106] Based on the cross-validation method, the behavioral pattern data is cross-validated using preliminary feature classification to generate verification results. The verification results and secondary feature classification are aggregated and analyzed through the data fusion algorithm to obtain the stability index.

[0107] The preliminary feature classification and behavior pattern data are verified by cross-validation. Specifically, the preliminary feature classification data is cross-validated with the behavior pattern data to evaluate the accuracy and consistency of the data. Then, the verification results and secondary feature classification are comprehensively analyzed using the data fusion algorithm to generate stability indicators to ensure the stability and reliability of the bandwidth allocation strategy.

[0108] For example, verify whether the bandwidth usage pattern of a port is consistent with the preliminary feature classification, and after comprehensive analysis through the data fusion algorithm, obtain the stability index of the port, indicating that its bandwidth usage is stable and reliable.

[0109] Hierarchical clustering is used to stratify the stability index data to obtain the classification index and stability strategy. Fuzzy logic is used to optimize the parameters of the classification index to obtain the basic scheduling strategy.

[0110] The stability indicators are analyzed in layers through the hierarchical clustering method. Specifically, the data is classified according to the stability indicators of each port to generate classification indicators and corresponding stability strategies. Then, the classification indicators are optimized through the fuzzy logic method, and the weights and priorities of each parameter are adjusted to obtain the basic scheduling strategy to ensure that the bandwidth allocation of each port can maintain the optimal state under different usage conditions.

[0111] For example, for some core ports, their stability index is high and their classification index is high priority. Their bandwidth allocation parameters are adjusted through fuzzy logic to ensure that they remain stable during high traffic periods.

[0112] The basic scheduling strategy is weightedly evaluated according to the entropy weight method, and strategy segmentation and strategy integration are generated based on the evaluation results. The strategy segmentation is encoded through hash mapping to obtain the strategy matrix, and the Block chain structure is used to optimize the strategy integration to obtain the integrated decision table.

[0113] The entropy weight method is used to perform a weighted evaluation of the basic scheduling strategy. Specifically, the weight of each strategy is calculated to determine its importance in the overall scheduling. Based on the evaluation results, the scheduling strategy is segmented and integrated, and the strategy segmentation results are encoded through hash mapping to generate a strategy matrix. The blockchain (Blockchain) structure is used to optimize the strategy integration to ensure the traceability and security of the strategy, and finally an optimized integrated decision table is obtained.

[0114] For example, after a weighted assessment of a strategy, if it is found that its weight is high, it will occupy an important position in the strategy matrix. It can be integrated and optimized through blockchain technology to ensure the accuracy and security of decision-making.

[0115] The policy matrix, integrated decision table and stability strategy are input into the preset deep neural network model. In the deep neural network model, the stability strategy is tuned based on the policy matrix and integrated decision table using convolution operations to obtain the traffic scheduling strategy.

[0116] By inputting the policy matrix, integrated decision table and stability strategy into the preset deep neural network model, specifically, using convolution operation to extract and tune the input data features, the final traffic scheduling strategy is generated to ensure the accuracy and efficiency of bandwidth allocation.

[0117] For example, a deep neural network can be used to analyze the bandwidth demand and traffic pattern of a port and generate an optimized traffic scheduling strategy to ensure optimal bandwidth utilization during peak hours.

[0118] The reliability of the traffic scheduling strategy is tested through Monte Carlo simulation, and the test analysis results are obtained.

[0119] The generated traffic scheduling strategy is tested for reliability through the Monte Carlo simulation method. Specifically, through a large number of random sampling and simulation runs, the performance of the traffic scheduling strategy in different network environments is evaluated, and the test analysis results are obtained to ensure the reliability and robustness of the strategy.

[0120] For example, by simulating network operation under different traffic load conditions, the effectiveness and stability of the traffic scheduling strategy can be evaluated to ensure its excellent performance in actual applications.

[0121] The test analysis results are compared with the real-time bandwidth usage monitored by the bandwidth monitoring module to obtain a comparison analysis result.

[0122] By comparing the test analysis results of the Monte Carlo simulation with the real-time monitoring data of the bandwidth monitoring module, specifically, comparing the actual usage and simulation results, the actual effect and accuracy of the traffic scheduling strategy are evaluated, and the comparison analysis results are generated to ensure the actual application effect of the strategy.

[0123] For example, through comparative analysis, it was found that the simulation results were highly consistent with the actual monitoring data, proving that the traffic scheduling strategy has high reliability in practical applications.

[0124] The comparison and analysis results are used as real-time feedback information and input into the bandwidth scheduling optimization module for real-time bandwidth scheduling optimization processing.

[0125] By inputting the comparison and analysis results as real-time feedback information into the bandwidth scheduling optimization module, specifically, using the feedback information to optimize and adjust the traffic scheduling strategy in real time, ensuring the optimal allocation of bandwidth resources and improving network performance.

[0126] For example, by analyzing the bandwidth usage of a port through real-time feedback, its bandwidth allocation strategy can be dynamically adjusted to ensure that the network can maintain efficient operation under different traffic conditions.

[0127] In this embodiment, the above steps are used to perform comprehensive bandwidth scheduling and optimization management on each port of the high-speed routing switching device. Specifically, the bandwidth requirements and priorities of each port are determined by real-time monitoring and classification of network traffic; statistical analysis and optimization algorithms are used to accurately calculate and dynamically adjust bandwidth allocation; and traffic scheduling strategies are generated and optimized through a variety of optimization algorithms and models to ensure efficient use of bandwidth resources and stable improvement of network performance. Ultimately, the generated bandwidth allocation and traffic scheduling strategies can effectively respond to different network environments and traffic changes, improve the overall performance and reliability of high-speed routing switching equipment, and meet users' needs for network bandwidth and stability. Example

[0128] like Figure 2 As shown, the present application also provides a bandwidth scheduling system 10 for high-speed routing switching, which is applied to high-speed routing switching equipment. The high-speed routing switching equipment includes a bandwidth monitoring module, a traffic scheduling module, a bandwidth allocation module and a bandwidth scheduling optimization module. The bandwidth scheduling system includes an analysis unit 11, a monitoring unit 12, an adjustment unit 13, an optimization unit 14, an allocation unit 15 and a scheduling unit 16.

[0129] The analysis unit 11 is mainly used to allocate bandwidth to each port of the high-speed routing switching device according to the network traffic, and analyze the initial bandwidth value of each port based on the allocation result.

[0130] The monitoring unit 12 is mainly used to monitor the real-time bandwidth usage of each port of the high-speed routing switching device using a bandwidth monitoring module to obtain the bandwidth usage rate of each port.

[0131] The adjustment unit 13 is mainly used to input all bandwidth utilization rates and all initial bandwidth values ​​into a preset scheduling algorithm model to obtain a bandwidth adjustment plan, and adjust and monitor the bandwidth of each port of the high-speed routing switching device based on the bandwidth adjustment plan to obtain an adjusted bandwidth utilization rate.

[0132] The optimization unit 14 is mainly used to dynamically optimize the bandwidth adjustment scheme based on the adjusted bandwidth usage rate, and generate a bandwidth allocation scheme based on the optimization result.

[0133] The allocation unit 15 is mainly used to input the bandwidth allocation scheme into the bandwidth allocation module to re-allocate bandwidth to each port of the high-speed routing switching device to obtain a bandwidth allocation result.

[0134] The scheduling unit 16 is mainly used to generate a traffic scheduling strategy based on the bandwidth allocation result, input the traffic scheduling strategy into the traffic scheduling module for configuration, compare the traffic scheduling strategy with the real-time bandwidth usage monitored by the bandwidth monitoring module to obtain the bandwidth scheduling comparison result, and input the bandwidth scheduling comparison result into the bandwidth scheduling optimization module for bandwidth scheduling optimization.

[0135] In this embodiment, the bandwidth management and traffic scheduling of high-speed routing switching equipment are fully optimized through the coordinated work of various units of the bandwidth scheduling system. Specifically, the analysis unit 11 first allocates bandwidth to each port according to the network traffic, and analyzes the initial bandwidth value of each port based on the allocation result. The monitoring unit 12 uses the bandwidth monitoring module to monitor the real-time bandwidth usage of each port to obtain the bandwidth utilization rate of each port. Then, the adjustment unit 13 inputs all bandwidth utilization rates and all initial bandwidth values ​​into the preset scheduling algorithm model, generates a bandwidth adjustment plan, and adjusts and monitors the bandwidth of each port based on the plan to obtain the adjusted bandwidth utilization rate. The optimization unit 14 dynamically optimizes the bandwidth adjustment plan according to the adjusted bandwidth utilization rate to generate a new bandwidth allocation plan. The allocation unit 15 inputs the new bandwidth allocation plan into the bandwidth allocation module, re-allocates the bandwidth to each port, and obtains a new bandwidth allocation result. Finally, the scheduling unit 16 generates a traffic scheduling strategy based on the bandwidth allocation result, inputs the traffic scheduling strategy into the traffic scheduling module for configuration, and compares the traffic scheduling strategy with the real-time bandwidth usage to obtain the bandwidth scheduling comparison result, and inputs it into the bandwidth scheduling optimization module for optimization and adjustment. The bandwidth scheduling system can monitor and adjust the bandwidth usage of each port in real time, dynamically optimize the bandwidth allocation strategy, and improve the utilization rate of bandwidth resources.

[0136] It should be noted that those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system and each unit described above can refer to the corresponding process in the aforementioned bandwidth scheduling method embodiment of high-speed routing switching, and will not be repeated here.

[0137] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A bandwidth scheduling method for high-speed routing switching, applied to a high-speed routing switching device, wherein the high-speed routing switching device comprises a bandwidth monitoring module, a traffic scheduling module, a bandwidth allocation module and a bandwidth scheduling optimization module, characterized in that: The bandwidth scheduling method comprises: Allocating bandwidth to each port of the high-speed routing switching device according to network traffic, and analyzing the initial bandwidth value of each port based on the allocation result; Using the bandwidth monitoring module to monitor the real-time bandwidth usage of each port of the high-speed routing switching device to obtain the bandwidth usage rate of each port; Inputting all the bandwidth utilization rates and all the initial bandwidth values ​​into a preset scheduling algorithm model to obtain a bandwidth adjustment plan, and adjusting and monitoring the bandwidth of each port of the high-speed routing switching device based on the bandwidth adjustment plan to obtain an adjusted bandwidth utilization rate; Dynamically optimizing the bandwidth adjustment scheme based on the adjusted bandwidth usage rate, and generating a bandwidth allocation scheme based on the optimization result; Inputting the bandwidth allocation scheme into the bandwidth allocation module to re-allocate bandwidth to each port of the high-speed routing switch device to obtain a bandwidth allocation result; A traffic scheduling strategy is generated based on the bandwidth allocation result, the traffic scheduling strategy is input into the traffic scheduling module for configuration, the traffic scheduling strategy is compared with the real-time bandwidth usage monitored by the bandwidth monitoring module to obtain a bandwidth scheduling comparison result, and the bandwidth scheduling comparison result is input into the bandwidth scheduling optimization module for bandwidth scheduling optimization.

2. The bandwidth scheduling method for high-speed routing switching according to claim 1, characterized in that: The step of allocating bandwidth to each port of the high-speed routing switching device according to network traffic, and analyzing the initial bandwidth value of each port based on the allocation result, comprises: The network traffic is collected through the network traffic monitor, and the network traffic is classified using the clustering algorithm to obtain the traffic of each category; Determining the bandwidth priority of each port according to the demand of each port of the high-speed routing switching device for each type of traffic; The bandwidth priorities are allocated bandwidth by a proportional allocation method to obtain allocation results, and the allocation results are statistically analyzed by a statistical analysis tool to obtain initial bandwidth values ​​of each port.

3. The bandwidth scheduling method for high-speed routing switching according to claim 1, characterized in that: The step of using the bandwidth monitoring module to monitor the real-time bandwidth usage of each port of the high-speed routing switching device to obtain the bandwidth usage rate of each port includes: The real-time data stream of each port of the high-speed routing switching device is collected by a data packet analysis tool to obtain the original bandwidth data of each port; The original bandwidth data of each port is preprocessed using data cleaning technology to obtain processed bandwidth data of each port, and the processed bandwidth data of each port is input into a preset calculation formula to calculate the bandwidth utilization rate of each port. The preset calculation formula is as follows: bandwidth utilization rate = (processed bandwidth data / maximum available bandwidth) × 100%.

4. The bandwidth scheduling method for high-speed routing switching according to claim 1, characterized in that: The step of inputting all the bandwidth utilization rates and all the initial bandwidth values ​​into a preset scheduling algorithm model to obtain a bandwidth adjustment scheme, adjusting and monitoring the bandwidth of each port of the high-speed routing switching device based on the bandwidth adjustment scheme, and obtaining the adjusted bandwidth utilization rate comprises: All the bandwidth usage rates are sorted and analyzed by statistical tools to obtain traffic distribution characteristics, congestion hotspot characteristics and traffic stability. The traffic distribution characteristics are analyzed by principal component analysis to obtain traffic peaks and traffic troughs. The congestion hotspot characteristics are processed based on the traffic peaks by time series analysis to obtain congestion frequency. The traffic trough is associated with the traffic stability by correlation coefficient method to obtain a stability index. Based on a preset linear programming model, the congestion frequency and the stability index are collaboratively optimized to generate a preliminary scheduling plan; All the initial bandwidth values ​​are arranged and grouped by bubble sort to obtain a high-demand bandwidth group and a low-demand bandwidth group, the high-demand bandwidth group is weighted adjusted by weighted summation method to obtain a priority-adjusted bandwidth, and the low-demand bandwidth group is processed by K-means clustering to obtain a stable allocated bandwidth; Comprehensively evaluating the priority adjustment bandwidth and the stable allocation bandwidth, generating a comprehensive bandwidth plan based on the evaluation result, and processing the preliminary scheduling plan and the comprehensive bandwidth plan using a greedy algorithm to obtain a bandwidth adjustment plan; Decomposing the bandwidth adjustment scheme by partial least squares method, generating key parameters, secondary parameters and auxiliary parameters based on the decomposition results, and performing secondary adjustment on the key parameters by using preset optimization rules to form first scheduling parameters and second scheduling parameters; According to the function optimal solution method, the first scheduling parameter and the secondary parameter are matched and optimized, and an adjustment index is generated based on the optimization result, and the distance between the second scheduling parameter and the auxiliary parameter is optimized using the Manhattan distance, and an adjustment vector is generated based on the optimization result; The adjustment index and the adjustment vector are combined and calculated by a constraint optimization method to obtain a bandwidth optimization matrix, and the bandwidth of each port of the high-speed routing switching device is adjusted using the bandwidth optimization matrix, and the adjusted bandwidth utilization rate is calculated based on the adjustment result.

5. The bandwidth scheduling method for high-speed routing switching according to claim 1, characterized in that: The step of dynamically optimizing the bandwidth adjustment scheme based on the adjusted bandwidth usage rate and generating a bandwidth allocation scheme based on the optimization result includes: Analyze the adjusted bandwidth usage rate based on statistical software to obtain a bandwidth usage rate analysis result; Iteratively optimizing the bandwidth adjustment scheme based on the bandwidth usage analysis result by using a particle swarm optimization algorithm to obtain an iterative bandwidth adjustment scheme; The iterated bandwidth adjustment scheme is optimized by using a dynamic adjustment strategy to obtain an optimization result, and the optimization result is smoothed by using a Kalman filter to obtain a bandwidth allocation scheme.

6. The bandwidth scheduling method for high-speed routing switching according to claim 1, characterized in that: The step of inputting the bandwidth allocation scheme into the bandwidth allocation module to re-allocate bandwidth to each port of the high-speed routing switching device to obtain a bandwidth allocation result includes: Performing path optimization analysis on the bandwidth allocation scheme using the shortest path algorithm, generating optimized allocation path information based on the analysis result, inputting the optimized allocation path information into the bandwidth allocation module, and in the bandwidth allocation module, allocating and executing the optimized allocation path information through the control instruction algorithm to obtain a first allocation result; Using a network performance monitoring tool to monitor and analyze the bandwidth usage of the bandwidth allocation scheme and the bandwidth usage of the first allocation result, to obtain first monitoring and analysis data and second monitoring and analysis data; Comparing the first monitoring and analysis data with the second monitoring and analysis data to generate a comparison and analysis result; The bandwidth allocation scheme is adjusted based on the comparison and analysis result by using a proportional-integral-differential control algorithm to obtain a bandwidth allocation result.

7. The bandwidth scheduling method for high-speed routing switching according to claim 1, characterized in that: The steps of generating a traffic scheduling strategy based on the bandwidth allocation result, inputting the traffic scheduling strategy into the traffic scheduling module for configuration, comparing the traffic scheduling strategy with the real-time bandwidth usage monitored by the bandwidth monitoring module to obtain a bandwidth scheduling comparison result, and inputting the bandwidth scheduling comparison result into the bandwidth scheduling optimization module for bandwidth scheduling optimization include: Classifying the bandwidth allocation results by support vector machine, generating feature set data and behavior pattern data based on the classification results, and grading the feature set data by analytic hierarchy process to generate preliminary feature grading and secondary feature grading; Based on the cross-validation method, the behavior pattern data is cross-validated using the preliminary feature classification to generate a validation result, and the validation result and the secondary feature classification are aggregated and analyzed by a data fusion algorithm to obtain a stability index; The stability index is stratified by hierarchical clustering to obtain a grading index and a stability strategy, and the grading index is optimized by fuzzy logic to obtain a basic scheduling strategy; Performing a weighted evaluation on the basic scheduling strategy according to the entropy weight method, generating strategy segmentation and strategy integration based on the evaluation result, encoding the strategy segmentation through hash mapping to obtain a strategy matrix, and optimizing the strategy integration structure using a Block chain structure to obtain an integrated decision table; Inputting the policy matrix, the integrated decision table and the stability policy into a preset deep neural network model, and in the deep neural network model, using convolution operation to tune the stability policy based on the policy matrix and the integrated decision table to obtain a traffic scheduling policy; Conduct reliability testing on the traffic scheduling strategy through Monte Carlo simulation to obtain test analysis results; Comparing the test analysis result with the real-time bandwidth usage monitored by the bandwidth monitoring module to obtain a comparison analysis result; The comparison and analysis results are used as real-time feedback information and input into the bandwidth scheduling optimization module for real-time bandwidth scheduling optimization processing.

8. A bandwidth scheduling system for high-speed routing switching, characterized in that: Applied to high-speed routing switching equipment, the high-speed routing switching equipment includes a bandwidth monitoring module, a traffic scheduling module, a bandwidth allocation module and a bandwidth scheduling optimization module, characterized in that the bandwidth scheduling system includes: An analysis unit, configured to allocate bandwidth to each port of the high-speed routing switching device according to network traffic, and to analyze an initial bandwidth value of each port based on the allocation result; A monitoring unit, used to monitor the real-time bandwidth usage of each port of the high-speed routing switching device using the bandwidth monitoring module to obtain the bandwidth usage rate of each port; An adjustment unit, configured to input all of the bandwidth utilization rates and all of the initial bandwidth values ​​into a preset scheduling algorithm model to obtain a bandwidth adjustment plan, and to adjust and monitor the bandwidth of each port of the high-speed routing switching device based on the bandwidth adjustment plan to obtain an adjusted bandwidth utilization rate; an optimization unit, configured to dynamically optimize the bandwidth adjustment scheme based on the adjusted bandwidth usage rate, and generate a bandwidth allocation scheme based on the optimization result; An allocation unit, configured to input the bandwidth allocation scheme into the bandwidth allocation module to re-allocate bandwidth to each port of the high-speed routing switching device to obtain a bandwidth allocation result; The scheduling unit is used to generate a traffic scheduling strategy based on the bandwidth allocation result, input the traffic scheduling strategy into the traffic scheduling module for configuration, compare the traffic scheduling strategy with the real-time bandwidth usage monitored by the bandwidth monitoring module to obtain a bandwidth scheduling comparison result, and input the bandwidth scheduling comparison result into the bandwidth scheduling optimization module for bandwidth scheduling optimization.

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