A communication network traffic management system

Abstract

The present invention relates to the technical field of traffic management, and specifically provides a communication network traffic management system. The system includes a traffic monitoring module, an abnormal traffic processing module, a traffic priority adjustment module, and a network load balancing module. In the present invention, by analyzing the distribution characteristics of communication data traffic in real time, abnormal data streams can be identified, and according to the impact of the abnormality, the abnormality level can be quantitatively evaluated. By locating the source node of the abnormal traffic and implementing bandwidth restrictions according to the abnormality level, the current limiting is more targeted, and the degree of current limiting can also be adjusted as needed, avoiding unnecessary broadband waste. When adjusting the priority of communication data by considering the importance of the service and real-time performance indicators, it ensures that the performance of critical applications is guaranteed first. By monitoring the node latency and packet loss in real time and intelligently adjusting the node bandwidth allocation according to the traffic priority, the overall operation efficiency and stability of the network are improved, and the network performance management is optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic management, and in particular, to a communication network traffic management system. Background Art

[0002] The technical field of traffic management focuses on effectively controlling and optimizing the transmission of data in a communication network to ensure the reasonable allocation and efficient use of network resources. It includes monitoring, controlling, and scheduling the flow of data packets in the network to optimize the overall performance and response time of the network. Traffic management achieves the guarantee of service quality through various mechanisms, such as bandwidth allocation, priority setting, congestion avoidance, and traffic shaping, and supports multiple service types and data streams. In addition, this field also covers cross-network traffic control, dealing with data transfer and management issues between different networks, and dynamic resource allocation technologies to cope with network state changes and the needs of different applications.

[0003] Among them, a communication network traffic management system is a system used to maintain and optimize the flow of data within a data network. The main purpose of the system is to ensure the stable operation of the network, prevent overload, improve data transmission efficiency, and guarantee the performance of critical applications. By real-time monitoring network traffic and making adjustments and controls according to preset rules, the traffic management system can dynamically allocate network bandwidth and resources, optimize the overall performance of the network, and ensure that all users and application programs obtain the necessary bandwidth and resources.

[0004] Traditional management systems lack sufficient dynamics and adaptability when dealing with network traffic. They rely on preset rules and static policies to adjust traffic, resulting in untimely responses or unreasonable resource allocation when the network state changes rapidly. For example, when a large amount of data streams burst out in the network, traditional systems cannot quickly identify and adjust priorities, resulting in the obstruction of critical services and affecting the user experience. In the traffic monitoring and management of traditional systems, relying on preset rules will lead to excessive or insufficient traffic control, resulting in waste of network resources and affecting the normal operation of services and data security. Summary of the Invention

[0005] The purpose of the present invention is to solve the drawbacks existing in the prior art, and to propose a communication network traffic management system.

[0006] To achieve the above purpose, the present invention adopts the following technical solution: A communication network traffic management system, the system includes:

[0007] The traffic monitoring module analyzes the distribution characteristics of communication data traffic based on network real-time communication data, identifies atypical traffic patterns, and evaluates the abnormal level according to the impact of abnormal traffic to obtain an abnormal traffic identification result;

[0008] Based on the abnormal traffic recognition result, the abnormal traffic processing module locates the source node of the abnormal traffic, restricts the bandwidth of the source node, and adjusts the current-limiting degree according to the abnormal level to obtain an abnormal handling record;

[0009] Based on the abnormal handling record, the traffic priority adjustment module adjusts the priority of the communication data, reconfigures the priority according to the service importance and real-time performance indicators of each type of traffic, and records the parameters and execution time of the adjustment operation to obtain a priority adjustment log;

[0010] Based on the priority adjustment log, the network load balancing module monitors the latency and packet loss data of each network node, evaluates the performance of the network nodes, and adjusts the bandwidth allocation of the network communication nodes in combination with the real-time load conditions and traffic priorities of the network nodes to obtain load balancing adjustment information.

[0011] The improvement of the present invention is that the method for identifying an atypical traffic pattern is as follows:

[0012] Based on the network real-time communication data, data traffic characteristics are extracted, including traffic volume, duration, frequency, etc., to obtain a data traffic characteristic data group;

[0013] Based on the data traffic characteristic data group, through the formula:

[0014] ;

[0015] Calculate the standard score of the data;

[0016] Among them, represents the traffic characteristic value of the th data point, represents the mean value, represents the standard deviation, is the standard score of the data, represents the total number of data points;

[0017] Based on the standard score of the data, it is compared with a preset standard threshold. If the standard score of the data is greater than the preset standard threshold, the data stream is marked as an atypical traffic pattern to obtain an atypical traffic pattern recognition result.

[0018] The improvement of the present invention is that the steps for obtaining the abnormal traffic recognition result are as follows:

[0019] Based on the atypical traffic pattern recognition result, the characteristic data of a single abnormal traffic event are extracted, including traffic peak, duration, and frequency, to obtain abnormal traffic correlation data;

[0020] Based on the abnormal traffic correlation data, through the formula:

[0021] ;

[0022] Evaluate the impact of abnormal traffic, calculate the abnormal level, and obtain the abnormal traffic identification result;

[0023] Among them, is the traffic peak value, is the duration, is the frequency, is the weight coefficient of the traffic peak value, is the weight coefficient of the duration, is the weight coefficient of the frequency, is the abnormal level.

[0024] The improvement of the present invention is that the method for locating the source node of abnormal traffic is:

[0025] Based on the abnormal traffic identification result, collect the packet information associated with the identified atypical traffic, including the source IP address and the destination IP address, to obtain the address association data;

[0026] Based on the address association data, perform frequency analysis on each source IP address, count the number of times each source IP address sends abnormal traffic, and through the formula:

[0027] ;

[0028] Calculate the traffic contribution rate of each source IP address;

[0029] Among them, is the total number of abnormal traffic events, is the traffic contribution rate, represents the number of abnormal traffic events sent from the source IP address;

[0030] Based on the traffic contribution rate of each source IP address, sort the traffic contribution rate values, and select the source IP address with the highest traffic contribution rate value as the source node to obtain the source node identification result.

[0031] The improvement of the present invention is that the steps for obtaining the abnormal handling record are:

[0032] Based on the source node identification result and the abnormal traffic identification result, extract the abnormal level, and through the formula:

[0033] ;

[0034] Calculate the bandwidth limit percentage;

[0035] Among them, is the abnormal level, is the basic coefficient for bandwidth adjustment, is the logarithmic adjustment coefficient, is the bandwidth limit percentage;

[0036] Based on the bandwidth limit percentage and the source node identification result, limit the bandwidth of the source node to obtain an exception handling record.

[0037] The improvement of the present invention is that the step of obtaining the priority adjustment log is as follows:

[0038] Based on the exception handling record, extract the service importance and real-time performance metrics of each type of traffic to obtain priority correlation data;

[0039] Based on the priority correlation data, through the formula:

[0040] ;

[0041] Calculate the priority of each type of traffic;

[0042] where, represents the service importance, represents the real-time performance, , and are weight coefficients, and are stability constants, is the traffic priority;

[0043] Based on the priority of each type of traffic, record the parameters and execution time of the adjustment operation to obtain a priority adjustment log.

[0044] The improvement of the present invention is that the method for evaluating the performance of network nodes is as follows:

[0045] Through a network monitoring tool, collect the delay and packet loss data of network nodes at a preset fixed interval to obtain network performance correlation data;

[0046] Based on the network performance correlation data, through the formula:

[0047] ;

[0048] Calculate the performance index of each network node to obtain the network node performance evaluation result;

[0049] where, is the packet loss rate of the node, is the delay of the node, and are adjustment parameters, is the performance index of the network node, is the base of the natural logarithm.

[0050] The present invention is improved in that the step of acquiring the load balancing adjustment information is:

[0051] Based on the priority adjustment log and the network node performance evaluation result, extract the performance index and traffic priority of the network node to obtain load association data;

[0052] Based on the load association data, by the formula:

[0053] ;

[0054] Calculate bandwidth adjustment percentage;

[0055] in, is the performance index of the network node, is the traffic priority, and To adjust the parameters, is the base of natural logarithms, Adjust the percentage for bandwidth;

[0056] Based on the bandwidth adjustment percentage, the bandwidth allocation of the network communication node to the data flow is adjusted to obtain load balancing adjustment information.

[0057] Compared with the prior art, the advantages and positive effects of the present invention are:

[0058] In the present invention, by real-time analysis of the distribution characteristics of communication data traffic, abnormal data flows can be identified, and the abnormal level can be quantitatively evaluated according to the abnormal impact. By locating the source node of the abnormal traffic and implementing bandwidth limitation according to the abnormal level, the flow limitation can be made more targeted, and the degree of flow limitation can be adjusted as needed to avoid unnecessary bandwidth waste. By considering the importance of the business and real-time performance indicators, the priority of communication data is adjusted to ensure the performance priority of key applications. By real-time monitoring of the node delay and packet loss, and intelligently adjusting the node bandwidth allocation according to the traffic priority, the overall operation efficiency and stability of the network are improved, and the network performance management is optimized. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 is a system flow chart of the present invention;

[0060] Figure 2 A flow chart for identifying atypical traffic patterns for the present invention;

[0061] Figure 3 A flow chart of obtaining abnormal traffic identification results according to the present invention;

[0062] Figure 4 A flow chart of locating the source node of abnormal traffic for the present invention;

[0063] Figure 5 This is the flowchart for obtaining the exception handling record of the present invention;

[0064] Figure 6 This is the flowchart for obtaining the priority adjustment log of the present invention;

[0065] Figure 7 This is the flowchart for evaluating the performance of network nodes in the present invention;

[0066] Figure 8 This is the flowchart for obtaining the load balancing adjustment information of the present invention. Detailed implementation manners

[0067] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0068] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by terms such as "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the accompanying drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention. In addition, in the description of the present invention, "a plurality of" means two or more unless otherwise specifically defined.

[0069] Please refer to Figure 1 , the present invention provides a technical solution: a communication network traffic management system, the system includes:

[0070] The traffic monitoring module analyzes the distribution characteristics of communication data traffic based on real-time network communication data, identifies atypical traffic patterns, and evaluates the anomaly level according to the impact of abnormal traffic to obtain the abnormal traffic identification result;

[0071] The abnormal traffic processing module locates the source node of the abnormal traffic based on the abnormal traffic identification result, restricts the bandwidth of the source node, and adjusts the current limiting degree according to the anomaly level to obtain the exception handling record;

[0072] The traffic priority adjustment module adjusts the priority of communication data based on the exception handling record, reconfigures the priority according to the service importance and real-time performance indicators of each type of traffic, and records the parameters and execution time of the adjustment operation to obtain the priority adjustment log;

[0073] The network load balancing module adjusts the log based on priorities, monitors the latency and packet loss data of each network node, evaluates the performance of the network nodes, and combines the real-time load conditions and traffic priorities of the network nodes to adjust the bandwidth allocation of the network communication nodes, obtaining load balancing adjustment information;

[0074] The abnormal traffic identification result includes the abnormal type, potential risk area, and abnormal level. The abnormal handling record includes the implemented flow limiting strategy and the adjusted bandwidth limit. The priority adjustment log includes the priority information before and after adjustment and the critical application traffic identifier. The load balancing adjustment information includes the node information after load balancing, the list of nodes involved in the adjustment, and the time point when the adjustment is implemented.

[0075] Please refer to Figure 2 , the method for identifying atypical traffic patterns is:

[0076] Based on the network real-time communication data, extract the data traffic characteristics, including traffic size, duration, frequency, etc., to obtain the data traffic characteristic data group;

[0077] Based on the data traffic characteristic data group, through the formula:

[0078] ;

[0079] Calculate the standard score of the data;

[0080] Among them, represents the traffic characteristic value of the th data point, represents the mean value, represents the standard deviation, is the standard score of the data, represents the total number of data points;

[0081] Based on the standard score of the data, compare it with the preset standard threshold. If the standard score of the data is greater than the preset standard threshold, mark the data stream as an atypical traffic pattern, obtaining the atypical traffic pattern identification result.

[0082] Formula:

[0083] ;

[0084] Detailed explanation of parameters and acquisition method:

[0085] : represents the traffic characteristic value of the th data point, such as traffic size or duration. These data points are obtained through a real-time network traffic monitoring system, usually directly exported from network management tools or APIs.

[0086] : represents the normal data point The average value is used to determine the central position of the data. It is obtained by summing all data points and then dividing by the total number of data points, that is obtained by .

[0087] : represents all data points The standard deviation, which is used to measure the degree of deviation of the data points from the average value. It is obtained by calculating the square root of the average value of the sum of the squares of the deviations of each data point from the average value, that is .

[0088] Calculation example:

[0089] Suppose five monitored data points are , and it is necessary to calculate the average value and standard deviation of these data points, and calculate the standard score .

[0090] Calculate the average value :

[0091] ;

[0092] Calculate the standard deviation :

[0093] ;

[0094] Calculate the standard score :

[0095] ;

[0096] The calculation result represents the sum of the standard scores of the atypical traffic patterns, and the scores are used to measure the abnormality of the data. A high value indicates that the monitored traffic pattern has a significant deviation compared with the normal pattern, indicating abnormal activities in the network.

[0097] Please refer to Figure 3 , the steps to obtain the abnormal traffic identification result are:

[0098] Based on the atypical traffic pattern recognition result, extract the characteristic data of a single abnormal traffic event, including the traffic peak, duration, and frequency, to obtain the abnormal traffic correlation data;

[0099] Based on the abnormal traffic correlation data, through the formula:

[0100] ;

[0101] Evaluate the impact of abnormal traffic, calculate the abnormal level, and obtain the abnormal traffic identification result;

[0102] Among them, is the traffic peak value, is the duration, is the frequency, is the weight coefficient of the traffic peak value, is the weight coefficient of the duration, is the weight coefficient of the frequency, is the abnormal level.

[0103] Formula:

[0104] ;

[0105] Detailed parameter explanation and acquisition method:

[0106] : The traffic peak value is the maximum data transfer rate recorded during network monitoring and is usually directly provided by network traffic analysis tools.

[0107] : The duration refers to the specific length of time that abnormal traffic persists and is also directly measured by the network monitoring system.

[0108] : The frequency represents the number of abnormal events that occur within the monitoring period and is recorded and calculated from event logs.

[0109] 、 、 : The weight coefficients are set according to the importance of each parameter's impact on the system in historical data. For example, in a network environment sensitive to traffic, may be set higher.

[0110] Calculation example:

[0111] Suppose a set of observed abnormal traffic data is as follows: Mbps (traffic peak value), seconds (duration), times / hour (frequency). The weight coefficients are set as: , , 。

[0112] Calculation process:

[0113] Calculate the weighted value of the traffic peak value:

[0114] ;

[0115] Calculate the weighted value of the duration:

[0116] ;

[0117] Calculate the weighted value of the frequency:

[0118] ;

[0119] Calculate :

[0120] ;

[0121] The calculated value is , which is obtained by comprehensively considering the influence of the traffic peak, duration, and frequency. A high value indicates a greater potential risk and corresponding security measures need to be taken.

[0122] Please refer to Figure 4 , the method for locating the source node of abnormal traffic is:

[0123] Based on the abnormal traffic identification result, collect the packet information associated with the identified atypical traffic, including the source IP address and the destination IP address, to obtain the address association data;

[0124] Based on the address association data, perform frequency analysis on each source IP address, count the number of times each source IP address sends abnormal traffic, through the formula:

[0125] ;

[0126] Calculate the traffic contribution rate of each source IP address;

[0127] Among them, is the total number of abnormal traffic events, is the traffic contribution rate, represents the number of abnormal traffic events sent from the source IP address;

[0128] Based on the traffic contribution rate of each source IP address, sort the traffic contribution rate values, and select the source IP address with the highest traffic contribution rate value as the source node to obtain the source node identification result.

[0129] Formula:

[0130] ;

[0131] Detailed explanation of parameters and acquisition methods:

[0132] : Represents the number of abnormal traffic events originating from the source IP address. This is calculated by analyzing the number of packets that match known abnormal patterns within a specified time window.

[0133] : The total number of abnormal traffic events, representing the quantity of all traffic events identified as abnormal during the observation window, statistically obtained from the traffic monitoring data of the entire network.

[0134] Calculation example:

[0135] Suppose within a monitoring window, a total of 100 abnormal traffic events are detected ( ), among which, the traffic events from IP address 192.168.1.1 are 20 times.

[0136] Calculation process:

[0137] Calculate the traffic contribution rate of a single source IP address 192.168.1.1 :

[0138] ;

[0139] The calculation result shows that IP address 192.168.1.1 contributes 20% of the abnormal traffic, meaning that the abnormal traffic originating from IP address 192.168.1.1 accounts for 20% of the total detected abnormal traffic. If this ratio is the highest among all source IPs, this IP address will be identified as the main source of abnormal traffic. In this way, network administrators can take measures such as bandwidth limitation against this source node to reduce its impact on the network.

[0140] Please refer to Figure 5 , the steps to obtain the abnormal handling record are as follows:

[0141] Based on the source node identification result and the abnormal traffic identification result, extract the abnormal level, through the formula:

[0142] ;

[0143] Calculate the bandwidth limitation percentage;

[0144] Among them, is the abnormal level, is the basic coefficient for bandwidth adjustment, is the logarithmic adjustment coefficient, is the bandwidth limitation percentage;

[0145] Based on the bandwidth limit percentage and the source node identification result, limit the bandwidth of the source node to obtain an exception handling record.

[0146] Formula:

[0147] ;

[0148] Detailed parameter explanations and acquisition methods:

[0149] : Exception level, obtained by calculation in the previous steps.

[0150] : Basic bandwidth adjustment coefficient, determined by the network security policy, used to balance the basic ratio of bandwidth adjustment. The coefficient is set based on the network capacity and historical security policies.

[0151] : Logarithmic adjustment coefficient, used to fine-tune the impact of the exception level on bandwidth limitation, ensuring that the bandwidth adjustment responds appropriately to the sensitivity of the exception level. The coefficient is customized according to past exception handling experience and network response requirements.

[0152] Calculation example:

[0153] Set the following parameter settings: Exception level , indicating that the identified traffic anomaly is severe, basic bandwidth adjustment coefficient , indicating that the network is very sensitive to abnormal traffic, adjustment coefficient , used to ensure that the logarithmic adjustment does not overreact due to small changes.

[0154] Calculation process:

[0155] Calculate the bandwidth limit percentage :

[0156] ;

[0157] The calculated bandwidth limit percentage means that the bandwidth of the source node will be reduced by approximately 22%. This adjustment reflects a relatively high exception level, and network administrators will adjust the egress bandwidth of the source node accordingly to mitigate the possible impact of abnormal traffic on the entire network.

[0158] Please refer to Figure 6 , and the steps to obtain the priority adjustment log are:

[0159] Extract the business importance and real-time performance metrics of each type of traffic based on the exception handling records to obtain the priority correlation data;

[0160] Based on the priority correlation data, through the formula:

[0161] ;

[0162] Calculate the priority of each type of traffic;

[0163] Among them, represents the business importance, represents the real-time performance, 、 and are weight coefficients, and are stability constants, is the traffic priority;

[0164] Based on the priority of each type of traffic, record the parameters and execution time of the adjustment operation to obtain the priority adjustment log.

[0165] Formula:

[0166] ;

[0167] Detailed parameter explanations and acquisition methods:

[0168] : Business importance, usually scored by the business department according to the impact of traffic on business operations. This parameter is directly obtained from business analysis data.

[0169] : Real-time performance metrics, including latency and bandwidth usage, calculated from real-time data provided by network monitoring tools.

[0170] 、 and : Weight coefficients, set according to the priorities of business and technical strategies to ensure a reasonable balance of the impacts of business importance and performance metrics.

[0171] and : Stability constants, used to ensure that the inside of the logarithmic function is always positive to avoid calculation errors, and usually a suitable value is determined based on historical data analysis, used to prevent the denominator from being zero and increase the mathematical stability of the formula, usually taking a very small positive number.

[0172] Calculation example:

[0173] Set the following parameter values: : Indicates that the traffic is of relatively high importance to the service. : Real-time performance metrics, such as low latency. , , : Weight coefficient, set according to the service strategy. : Ensures the positive value of the logarithm. : A small constant to prevent division-by-zero errors.

[0174] Calculation process:

[0175] Calculate the value inside the logarithmic function:

[0176] ;

[0177] Apply the logarithm and the weight coefficient:

[0178] ;

[0179] The calculated priority , indicating that under the given service importance and real-time performance metrics, the traffic should be given a relatively low priority for network resources. The value helps network administrators adjust the configurations of routers and switches, optimize network performance, and ensure that the traffic of critical services is given priority.

[0180] Please refer to Figure 7 , the method for evaluating the performance of network nodes is:

[0181] Collect the delay and packet loss data of network nodes at preset fixed intervals through network monitoring tools to obtain network performance correlation data;

[0182] Based on the network performance correlation data, through the formula:

[0183] ;

[0184] Calculate the performance index of each network node to obtain the network node performance evaluation result;

[0185] Among them, is the packet loss rate of the node, is the delay of the node, and are adjustment parameters, is the performance index of the network node, is the base of the natural logarithm.

[0186] Formula:

[0187] ;

[0188] Parameter details and acquisition methods:

[0189] : The packet loss rate of the node, which is real-time data directly obtained from the network performance monitoring tool. It reflects the proportion of packets lost by the network node during data transmission.

[0190] : The latency of the node, in milliseconds, and is also monitored in real-time through the network monitoring tool. Latency refers to the time required for data to travel from the sending point to the receiving point and is one of the key metrics for evaluating network performance.

[0191] and : The adjustment parameter is used to balance the influence of the packet loss rate and latency in performance evaluation. The value of the coefficient is optimized based on historical performance data and specific network requirements to ensure that the evaluation result can accurately reflect the performance status of the node.

[0192] Calculation example:

[0193] Set the following parameter values: (5% packet loss rate), (100 milliseconds latency), , (adjustment coefficient).

[0194] Calculate the expression inside the exponential function:

[0195] ;

[0196] Calculate :

[0197] ;

[0198] The calculated performance index , indicating that the performance evaluation result of the node is close to neutral, reflecting the actual performance of the node under the current network conditions.

[0199] Please refer to Figure 8 , and the steps to obtain the load balancing adjustment information are as follows:

[0200] Based on the priority adjustment log and the network node performance evaluation result, extract the performance index and traffic priority of the network node to obtain the load-related data;

[0201] Based on the load-related data, through the formula:

[0202] ;

[0203] Calculate the bandwidth adjustment percentage;

[0204] Wherein, is the performance index of the network node, is the traffic priority, and are adjustment parameters, is the base of the natural logarithm, is the bandwidth adjustment percentage;

[0205] Based on the bandwidth adjustment percentage, adjust the bandwidth allocation of the network communication node to the data stream to obtain the load balancing adjustment information.

[0206] Formula:

[0207] ;

[0208] Detailed explanation and acquisition method of parameters:

[0209] : The performance index of the network node, obtained by calculation in the previous step.

[0210] : The traffic priority, obtained by calculation in the previous step.

[0211] and : Adjustment parameters, which are the weight coefficient and offset specifically for adjusting the influence of traffic priority. For enhancing the direct influence of the priority while is used to adjust the offset of the reaction to the bandwidth adjustment, so as to provide sensitivity control for the reaction to the bandwidth adjustment.

[0212] Calculation example:

[0213] Set the following parameter values: : Indicates that the node has high performance. : Indicates that the traffic has medium service priority. : Strengthens the influence of the priority. : Provides a baseline offset for the reaction.

[0214] Calculate the expression inside the exponential function:

[0215] ;

[0216] Calculate :

[0217] ;

[0218] Calculated bandwidth adjustment percentage , indicating that under the given performance index and traffic priority, the network node should be close to 50% bandwidth allocation. This result shows that the node can handle nearly half of the network bandwidth under its current performance and traffic priority conditions. The calculation helps network administrators dynamically adjust the bandwidth allocation of each node, optimize the resource usage of the entire network, and improve service quality and response speed.

[0219] The above are only the preferred embodiments of the present invention, and are not intended to limit the present invention in other forms. Any person skilled in the art may use the disclosed technical content to make changes or modifications into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change, and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution content of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. A communication network traffic management system, characterized in that: The system comprises: The traffic monitoring module analyzes the distribution characteristics of communication data traffic based on real-time network communication data, identifies atypical traffic patterns, and evaluates the abnormal level according to the impact of abnormal traffic to obtain abnormal traffic identification results; The abnormal traffic processing module locates the source node of the abnormal traffic based on the abnormal traffic identification result, limits the bandwidth of the source node, and adjusts the flow limitation degree according to the abnormal level to obtain an abnormal processing record; The traffic priority adjustment module adjusts the priority of the communication data based on the exception processing record, reconfigures the priority according to the business importance and real-time performance indicators of each traffic, and records the parameters and execution time of the adjustment operation to obtain a priority adjustment log; The network load balancing module monitors the delay and packet loss data of each network node based on the priority adjustment log, evaluates the performance of the network node, and adjusts the bandwidth allocation of the network communication node in combination with the real-time load situation and traffic priority of the network node to obtain load balancing adjustment information.

2. The communication network traffic management system according to claim 1, characterized in that: The method for identifying atypical traffic patterns is: Based on the real-time network communication data, extract data flow characteristics, including flow size, duration, and frequency, to obtain a data flow characteristic data group; Based on the data flow characteristic data group, through the formula: ； Calculate standard scores for the data; in, Indicates The flow characteristic value of the data point, represents the mean, represents the standard deviation, is the standard score of the data, Indicates the total number of data points; Based on the standard score of the data, it is compared with a preset standard threshold. If the standard score of the data is greater than the preset standard threshold, the data flow is marked as an atypical traffic pattern, and an atypical traffic pattern recognition result is obtained.

3. The communication network traffic management system according to claim 2, characterized in that: The steps for obtaining the abnormal traffic identification result are: Based on the atypical traffic pattern recognition result, characteristic data of a single abnormal traffic event is extracted, including traffic peak value, duration and frequency, to obtain abnormal traffic correlation data; Based on the abnormal traffic correlation data, the formula is: ； Evaluate the impact of abnormal traffic, calculate the abnormal level, and obtain abnormal traffic identification results; in, is the peak flow rate, is the duration, is the frequency, is the weight coefficient of the traffic peak, is the weight coefficient of duration, is the frequency weight coefficient, It is an abnormal level.

4. The communication network traffic management system according to claim 1, characterized in that: The method for locating the source node of abnormal traffic is: Based on the abnormal traffic identification result, data packet information associated with the identified atypical traffic is collected, including source IP addresses and destination IP addresses, to obtain address association data; Based on the address association data, frequency analysis is performed on each source IP address, and the number of times each source IP address sends abnormal traffic is counted, using the formula: ； Calculate the traffic contribution rate of each source IP address; in, is the total number of abnormal traffic events, is the traffic contribution rate, Indicates the number of abnormal traffic events sent from the source IP address; Based on the traffic contribution rate of each source IP address, the traffic contribution rate values ​​are sorted, and the source IP address with the highest traffic contribution rate value is selected as the source node to obtain the source node identification result.

5. The communication network traffic management system according to claim 4, characterized in that: The steps for obtaining the exception handling record are: Based on the source node identification results and abnormal traffic identification results, the abnormal level is extracted through the formula: ； Calculate bandwidth limit percentage; in, For abnormal level, is the basic coefficient for bandwidth adjustment, is the logarithmic adjustment coefficient, is the bandwidth limit percentage; Based on the bandwidth limitation percentage and the source node identification result, the bandwidth of the source node is limited to obtain an exception processing record.

6. The communication network traffic management system according to claim 1, characterized in that: The steps for obtaining the priority adjustment log are: Based on the exception handling records, extract the business importance and real-time performance indicators of each type of traffic to obtain priority-related data; Based on the priority association data, by the formula: ； Calculate the priority of each type of traffic; in, Represents business importance, Represents real-time performance, , and is the weight coefficient, and is the stability constant, is the traffic priority; Based on the priority of each type of traffic, the parameters and execution time of the adjustment operation are recorded to obtain a priority adjustment log.

7. The communication network traffic management system according to claim 1, characterized in that: The method for evaluating network node performance is: Through network monitoring tools, the delay and packet loss data of network nodes are collected at preset fixed intervals to obtain network performance correlation data; Based on the network performance correlation data, through the formula: ； Calculate the performance index of each network node to obtain the network node performance evaluation result; in, is the data packet loss rate of the node, is the node delay, and To adjust the parameters, is the performance index of the network node, is the base of natural logarithms.

8. The communication network traffic management system according to claim 7, characterized in that: The steps for obtaining the load balancing adjustment information are as follows: Based on the priority adjustment log and the network node performance evaluation result, extract the performance index and traffic priority of the network node to obtain load association data; Based on the load association data, by the formula: ； Calculate bandwidth adjustment percentage; in, is the performance index of the network node, is the traffic priority, and To adjust the parameters, is the base of natural logarithms, Adjust the percentage for bandwidth; Based on the bandwidth adjustment percentage, the bandwidth allocation of the network communication node to the data flow is adjusted to obtain load balancing adjustment information.

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