Dynamic traffic scheduling method and system based on SD-WAN technology

Abstract

The invention discloses a dynamic traffic scheduling method and system based on an SD-WAN technology, which can timely discover potential problems in a network by monitoring performance parameters of network links and nodes in real time, and can effectively relieve network congestion and improve the overall network performance based on analysis of the performance parameters and dynamic adjustment of network routing and bandwidth allocation strategies. According to the method, a high-flow time period, a low-flow time period and key service flow are identified, so that the distribution of network resources is more reasonable and efficient, the adjusted network performance is evaluated in real time, the expected effect of each adjustment can be ensured, and if the performance does not reach a preset standard, the scheduling strategy is continuously optimized, and the scheduling efficiency is improved. According to the technical scheme, the method is beneficial to adapting to rapidly changing network environments and service requirements, the stability and reliability of the network are enhanced, the network states, scheduling strategies and performance evaluation results before and after adjustment are recorded in logs, and operation and maintenance personnel can rapidly position network problems by analyzing log data, so that the operation and maintenance efficiency and accuracy are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of dynamic traffic scheduling, and in particular to a dynamic traffic scheduling method and system based on SD-WAN technology. Background Art

[0002] With the global expansion of corporate business and the popularization of cloud computing technology, the traditional WAN (Wide Area Network) architecture has been unable to meet the needs of modern enterprises for network flexibility, scalability and high availability. The traditional WAN architecture usually relies on static, predefined routing and bandwidth allocation methods, which is difficult to cope with complex and changing network environments and business demand changes. Especially in multi-cloud and hybrid cloud environments, enterprises need to efficiently transmit data between different geographical locations and different operator networks to ensure business continuity and data security.

[0003] SD-WAN (Software Defined Wide Area Network) technology came into being. By separating the network control plane from the data forwarding plane, it realizes centralized management and flexible scheduling of network resources. SD-WAN technology can dynamically adjust network routing, bandwidth allocation and other parameters according to business needs and network conditions, improve the utilization efficiency of network resources, reduce network costs, and improve the overall performance and reliability of the network.

[0004] However, in SD-WAN networks, how to efficiently schedule and manage network traffic remains a challenge. Traditional traffic scheduling methods often rely on fixed rules or experience and cannot adapt to rapidly changing network environments and business needs. Especially in high-concurrency, high-traffic business scenarios, traditional scheduling methods are prone to network congestion, increased latency, increased packet loss rates and other problems, affecting user experience and business continuity. Summary of the invention

[0005] In view of this, the present invention proposes a dynamic traffic scheduling method and system based on SD-WAN technology, which can solve the defects of the prior art that it cannot adapt to the rapidly changing network environment and business needs, and easily cause network congestion, increased delay, and increased packet loss rate.

[0006] The technical solution of the present invention is achieved in this way:

[0007] A dynamic traffic scheduling method based on SD-WAN technology, specifically comprising:

[0008] Real-time monitoring of the performance parameters of each link and node in the SD-WAN network;

[0009] Based on the monitored performance parameters, the preset algorithm is used to analyze the network traffic pattern to identify high-traffic periods, low-traffic periods and key business traffic;

[0010] Dynamically adjust network routing and bandwidth allocation strategies based on traffic pattern analysis results;

[0011] Evaluate the adjusted network performance in real time. If the performance does not meet the preset standard, continue to optimize the scheduling strategy until the performance requirements are met.

[0012] The network status, scheduling strategy and performance evaluation results before and after the adjustment are recorded in the log.

[0013] As a further optional solution of the dynamic traffic scheduling method based on SD-WAN technology, the real-time monitoring of the performance parameters of each link and node in the SD-WAN network specifically includes:

[0014] Deploy monitoring probes on key nodes and links of the SD-WAN network;

[0015] The key performance parameters of each link and node are collected in real time based on monitoring probes, including bandwidth utilization, delay, jitter, packet loss rate and error rate;

[0016] For key business traffic, DPI technology is used to conduct in-depth analysis of key performance parameters to identify application type information and user behavior information;

[0017] The collected key performance parameters are integrated with the application type information and user behavior information identified by DPI technology to form performance parameters for each link and node.

[0018] As a further optional solution of the dynamic traffic scheduling method based on SD-WAN technology, the method uses a preset algorithm to analyze the network traffic pattern according to the monitored performance parameters to identify high traffic periods, low traffic periods and key business traffic, specifically including:

[0019] Extract traffic pattern features based on the monitored performance parameters to obtain traffic statistical features, traffic trend features, and traffic periodicity features;

[0020] Use time series analysis algorithms to predict traffic statistics, traffic trends, and traffic periodicity to identify future high and low traffic periods;

[0021] By combining the application type information and user behavior information identified by DPI technology, as well as statistical characteristics, trend characteristics, and periodic characteristics, key business traffic can be identified.

[0022] As a further optional solution of the dynamic traffic scheduling method based on SD-WAN technology, the traffic pattern feature extraction is performed based on the monitored performance parameters to obtain traffic statistical features, traffic trend features and traffic periodic features, specifically including:

[0023] Calculate the average bandwidth utilization, peak bandwidth, total traffic, and packet loss rate in each time window to obtain traffic statistics characteristics;

[0024] Using the sliding window method, the trend of traffic changes is calculated, the upward or downward trend is identified, and the traffic trend characteristics are obtained;

[0025] The periodic patterns in the flow data are identified by Fourier transform, and the periodic characteristics of the flow are obtained.

[0026] As a further optional solution of the dynamic traffic scheduling method based on SD-WAN technology, the dynamic adjustment of network routing and bandwidth allocation strategy based on the traffic pattern analysis result specifically includes:

[0027] Formulate a scheduling strategy, wherein the scheduling strategy includes a bandwidth reservation strategy, a routing optimization strategy, and a load balancing strategy;

[0028] Deploy the developed scheduling strategy to network devices and control systems;

[0029] Network equipment and control systems continuously monitor key performance parameters and match corresponding scheduling strategies based on the analysis results of high-traffic periods, low-traffic periods and key business traffic.

[0030] Dynamically adjust network routing and bandwidth allocation strategies based on the matching scheduling strategy.

[0031] As a further optional solution of the dynamic traffic scheduling method based on SD-WAN technology, the real-time evaluation of the adjusted network performance, if the performance does not meet the preset standard, continues to optimize the scheduling strategy until the performance requirements are met, specifically includes:

[0032] Use network monitoring tools to collect adjusted network performance data in real time;

[0033] Analyze the collected data in real time and calculate the current network performance index value;

[0034] Compare the calculated performance index values ​​with the preset standards to determine whether the network performance meets the standards. If all performance indicators meet or exceed the preset standards, the current network performance is considered good and no further adjustment is required. Otherwise, analyze the shortcomings of the current scheduling strategy and identify the key factors that lead to substandard performance.

[0035] According to the analysis results, the scheduling strategy is adjusted accordingly;

[0036] The further adjusted scheduling strategy is deployed to network devices and control systems.

[0037] A dynamic traffic scheduling system based on SD-WAN technology, comprising:

[0038] Real-time monitoring module, used to monitor the performance parameters of each link and node in the SD-WAN network in real time;

[0039] The traffic pattern analysis module is connected to the real-time monitoring module, and is used to receive the monitored performance parameters and analyze the network traffic pattern using a preset algorithm to identify high-traffic periods, low-traffic periods, and key business traffic;

[0040] A policy adjustment module, connected to the traffic pattern analysis module, for dynamically adjusting network routing and bandwidth allocation policies based on the results of the traffic pattern analysis module;

[0041] A performance evaluation module, connected to the policy adjustment module, for evaluating the adjusted network performance in real time;

[0042] The scheduling optimization module is connected to the performance evaluation module. When the performance evaluation module determines that the network performance does not meet the preset standard, the scheduling optimization module is triggered to continue optimizing the scheduling strategy until the performance requirements are met.

[0043] As a further optional solution of the dynamic traffic scheduling system based on SD-WAN technology, the system also includes:

[0044] The logging module is used to record the network status, scheduling strategy and performance evaluation results before and after the adjustment.

[0045] A computing device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned dynamic traffic scheduling method based on SD-WAN technology are implemented.

[0046] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-mentioned dynamic traffic scheduling method based on SD-WAN technology.

[0047] The beneficial effects of the present invention are as follows: by real-time monitoring of the performance parameters of network links and nodes, bottlenecks and potential problems in the network can be discovered in time; based on the analysis of performance parameters, the network routing and bandwidth allocation strategies can be dynamically adjusted, network congestion can be effectively alleviated, and overall network performance can be improved, including reducing delay, reducing packet loss rate, improving bandwidth utilization, etc.; identifying high-traffic periods, low-traffic periods and key business traffic, making the allocation of network resources more reasonable and efficient; reserving sufficient bandwidth resources for key business traffic during high-traffic periods to ensure that the service quality of key businesses is not affected; and avoiding wasting bandwidth resources during non-critical periods; evaluating the adjusted network performance in real time to ensure that each adjustment can achieve the expected effect; if the performance does not meet the preset standard, continuing to optimize the scheduling strategy; this continuous optimization process helps to adapt to the rapidly changing network environment and business needs, enhance the stability and reliability of the network, and reduce the impact of network failures or performance fluctuations on the business; the network status before and after the adjustment, the scheduling strategy and the performance evaluation results are recorded in the log, providing rich data support for network operation and maintenance personnel; the operation and maintenance personnel can quickly locate network problems by analyzing the log data, and formulate targeted optimization plans, thereby improving the efficiency and accuracy of operation and maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] 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 work.

[0049] Figure 1 A flow chart of a dynamic traffic scheduling method based on SD-WAN technology of the present invention;

[0050] Figure 2 This is a schematic diagram of the composition of a dynamic traffic scheduling system based on SD-WAN technology in the present invention. DETAILED DESCRIPTION

[0051] The technical solutions in the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only 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.

[0052] refer to Figure 1 to Figure 2 , a dynamic traffic scheduling method based on SD-WAN technology, specifically including:

[0053] Real-time monitoring of the performance parameters of each link and node in the SD-WAN network;

[0054] Based on the monitored performance parameters, the preset algorithm is used to analyze the network traffic pattern to identify high-traffic periods, low-traffic periods and key business traffic;

[0055] Dynamically adjust network routing and bandwidth allocation strategies based on traffic pattern analysis results;

[0056] Evaluate the adjusted network performance in real time. If the performance does not meet the preset standard, continue to optimize the scheduling strategy until the performance requirements are met.

[0057] The network status, scheduling strategy and performance evaluation results before and after the adjustment are recorded in the log.

[0058] In this embodiment, by real-time monitoring of the performance parameters of network links and nodes, bottlenecks and potential problems in the network can be discovered in time. Based on the analysis of performance parameters, the network routing and bandwidth allocation strategies are dynamically adjusted, which can effectively alleviate network congestion and improve overall network performance, including reducing delays, reducing packet loss rates, and improving bandwidth utilization. High-traffic periods, low-traffic periods, and key business traffic are identified to make the allocation of network resources more reasonable and efficient. Sufficient bandwidth resources are reserved for key business traffic during high-traffic periods to ensure that the service quality of key businesses is not affected, while avoiding wasting bandwidth resources during non-critical periods. The adjusted network performance is evaluated in real time to ensure that each adjustment can achieve the expected effect. If the performance does not meet the preset standard, the scheduling strategy is continuously optimized. This continuous optimization process helps to adapt to the rapidly changing network environment and business needs, enhance the stability and reliability of the network, and reduce the impact of network failures or performance fluctuations on the business. The network status before and after the adjustment, the scheduling strategy, and the performance evaluation results are recorded in the log, providing rich data support for network operation and maintenance personnel. The operation and maintenance personnel can quickly locate network problems by analyzing the log data and formulate targeted optimization plans, thereby improving the efficiency and accuracy of operation and maintenance.

[0059] Preferably, the real-time monitoring of the performance parameters of each link and node in the SD-WAN network specifically includes:

[0060] Deploy monitoring probes on key nodes and links of the SD-WAN network;

[0061] The key performance parameters of each link and node are collected in real time based on monitoring probes, including bandwidth utilization, delay, jitter, packet loss rate and error rate;

[0062] For key business traffic, DPI technology is used to conduct in-depth analysis of key performance parameters to identify application type information and user behavior information;

[0063] The collected key performance parameters are integrated with the application type information and user behavior information identified by DPI technology to form performance parameters for each link and node.

[0064] In this embodiment, monitoring probes are deployed on key nodes and links of the SD-WAN network to achieve refined monitoring of key parts of the network. This targeted monitoring strategy helps to quickly locate potential network problems and improve monitoring efficiency. Key performance parameters such as bandwidth utilization, latency, jitter, packet loss rate and error rate collected in real time by monitoring probes provide a rich data basis for comprehensive evaluation of network performance. These parameters can comprehensively reflect the actual operation status of the network and provide an accurate basis for subsequent traffic pattern analysis and scheduling strategy formulation. DPI (deep packet inspection) technology is used to conduct in-depth analysis of key business traffic and identify application type information and user behavior information. This in-depth analysis not only helps to understand the business traffic, but also helps to identify the application type information and user behavior information. The specific composition can also provide insights into users' network usage habits and business needs, providing strong support for network optimization and service quality assurance; the collected key performance parameters are integrated with the application type information and user behavior information identified by DPI technology to form a comprehensive performance evaluation of each link and node. This comprehensive evaluation not only takes into account the performance indicators at the network level, but also incorporates information at the business level, making the evaluation results more comprehensive and accurate; based on the above comprehensive performance evaluation results, the network management system can formulate and adjust scheduling strategies more intelligently. For example, after identifying high-traffic periods and critical business traffic, the system can automatically adjust routing and bandwidth allocation strategies to ensure the smooth operation of critical businesses and optimization of overall network performance.

[0065] It should be noted that for key business traffic, DPI technology is used to conduct in-depth analysis of key performance parameters to identify application type information and user behavior information, including:

[0066] DPI devices capture data packets passing through the network in real time, including data packets of critical business traffic;

[0067] First, the DPI system parses the header information of the data packet to obtain basic information such as source address, destination address, port number, protocol type, etc. This information is crucial for subsequent traffic classification and routing decisions;

[0068] In addition to the header information, the DPI system also deeply analyzes the payload of the data packet, that is, the actual content of the data packet, which is the key difference between DPI technology and traditional packet filtering technology;

[0069] Identify the application type by matching the captured data packet features with the patterns in the feature library;

[0070] Conduct in-depth protocol analysis to more accurately identify application types. For example, by analyzing the URL of an HTTP request or the subject and content of an SMTP email, you can identify the website a user is visiting or the type of email they are sending.

[0071] Identify application types and user behaviors by analyzing user behavior patterns. For example, by analyzing the user's access frequency, access duration, and access content within a specific time period, the user's online habits, interests, and hobbies can be inferred;

[0072] Detect abnormal behaviors in the network, such as abnormal traffic patterns, unauthorized application access, etc. These abnormal behaviors may be precursors to network attacks, and the DPI system can detect and alarm in time;

[0073] The identified application type information and user behavior information are output to the network administrator or related management system. This information is usually presented in the form of reports, charts, etc., which is convenient for network administrators to understand and analyze.

[0074] Preferably, the method of analyzing the network traffic pattern using a preset algorithm based on the monitored performance parameters to identify high traffic periods, low traffic periods and key business traffic specifically includes:

[0075] Extract traffic pattern features based on the monitored performance parameters to obtain traffic statistical features, traffic trend features, and traffic periodicity features;

[0076] Use time series analysis algorithms to predict traffic statistics, traffic trends, and traffic periodicity to identify future high and low traffic periods;

[0077] By combining the application type information and user behavior information identified by DPI technology, as well as statistical characteristics, trend characteristics, and periodic characteristics, key business traffic can be identified.

[0078] In this embodiment, by extracting traffic statistical features, traffic trend features and traffic periodic features, the technical solution can more comprehensively and deeply understand the changing patterns of network traffic. These features not only reflect the current state of the traffic, but also reveal its future development trends and periodic fluctuations, providing a solid foundation for subsequent traffic pattern recognition. The extracted features are predicted by a time series analysis algorithm, which can accurately identify future high-traffic periods and low-traffic periods. This prediction capability enables the network management system to respond in advance by adjusting routing and bandwidth allocation strategies to cope with upcoming traffic peaks or troughs, thereby ensuring the smooth operation of the network. Combined with the application type information and user behavior information identified by the DPI technology, as well as statistical features, trend features, and periodic features, the technical solution can further identify key business traffic. This identification capability helps the network management system to give higher priority to key businesses. priority and better service quality assurance to ensure the stable operation and efficient transmission of key businesses in the network; based on the above traffic pattern recognition results, the network management system can make more intelligent scheduling decisions. For example, when high traffic periods are predicted, the system can automatically adjust the routing strategy to guide key business traffic to links with better performance. During low traffic periods, some bandwidth resources can be released for use by other non-critical businesses. This intelligent scheduling decision helps to improve the utilization efficiency of network resources and reduce operating costs; by real-time monitoring and analysis of network traffic patterns, this technical solution helps network managers to more accurately understand the allocation and utilization efficiency of network resources. Based on this information, managers can adjust the configuration plan of network resources in a timely manner to meet changes in business needs and the sustainable development of the network; identifying and ensuring the service quality of key business traffic can significantly improve the user's network experience.

[0079] Preferably, the flow pattern feature extraction is performed based on the monitored performance parameters to obtain flow statistical features, flow trend features and flow periodic features, specifically including:

[0080] Calculate the average bandwidth utilization, peak bandwidth, total traffic, and packet loss rate in each time window to obtain traffic statistics characteristics;

[0081] Using the sliding window method, the trend of traffic changes is calculated, the upward or downward trend is identified, and the traffic trend characteristics are obtained;

[0082] The periodic patterns in the flow data are identified by Fourier transform, and the periodic characteristics of the flow are obtained.

[0083] In this embodiment, by calculating traffic statistical characteristics such as average bandwidth utilization, peak bandwidth, total traffic and packet loss rate in each time window, the technical solution can quantitatively describe the current state of network traffic. These statistical characteristics not only reflect the utilization of network resources, but also provide important data support for subsequent traffic pattern analysis and prediction; the trend of traffic change is calculated using the sliding window method, which can capture the dynamic process of traffic increase or decrease in real time. This trend insight capability helps the network management system to perceive traffic changes in advance and make corresponding scheduling decisions. At the same time, based on trend characteristics, time series analysis and other methods can also be used to predict future traffic, providing strong support for network planning and optimization; by identifying periodic patterns in traffic data through signal processing technologies such as Fourier transform, the periodic change law of network traffic can be revealed. This periodic feature not only helps to understand the internal mechanism of network traffic, but also provides a basis for the periodic scheduling and optimization of network resources. For example, maintenance or upgrade operations during the period of low network traffic can reduce the impact on the business, and increasing bandwidth resources in advance during peak hours can ensure the smooth operation of key businesses. Based on the extracted traffic statistical characteristics, trend characteristics and periodic characteristics, the network management system can make more intelligent scheduling decisions. For example, after identifying the peak traffic period, the system can automatically adjust the routing strategy to balance the network load. When periodic traffic changes are found, the corresponding resource allocation plan can be prepared in advance. This intelligent scheduling and management method helps to improve the overall performance of the network and user experience.

[0084] Preferably, the dynamically adjusting network routing and bandwidth allocation strategies based on the traffic pattern analysis results specifically includes:

[0085] Formulate a scheduling strategy, wherein the scheduling strategy includes a bandwidth reservation strategy, a routing optimization strategy, and a load balancing strategy;

[0086] Deploy the developed scheduling strategy to network devices and control systems;

[0087] Network equipment and control systems continuously monitor key performance parameters and match corresponding scheduling strategies based on the analysis results of high-traffic periods, low-traffic periods and key business traffic.

[0088] Dynamically adjust network routing and bandwidth allocation strategies based on the matching scheduling strategy.

[0089] In this embodiment, by formulating scheduling strategies including bandwidth reservation strategy, route optimization strategy and load balancing strategy, and dynamically adjusting according to the real-time traffic pattern analysis results, the technical solution significantly improves the flexibility and responsiveness of the network. This dynamic adjustment can quickly adapt to changes in network traffic and ensure efficient use of network resources and business continuity. During high traffic periods, the bandwidth reservation strategy is used to ensure that the bandwidth requirements of key business traffic are met. At the same time, the load balancing strategy is used to balance the network load to avoid overloading of a single link or node. During low traffic periods, part of the reserved bandwidth can be released for use by other non-critical businesses to achieve optimal configuration of network resources. Combined with the application type information and user behavior information identified by the DPI technology, the technical solution can formulate a special scheduling strategy for key business traffic to ensure the priority and service quality of these businesses in the network. This differentiated service strategy helps to improve user experience and meet the high availability and high reliability requirements of enterprises for key businesses. The network equipment and control system continuously monitor key performance parameters. Once a network anomaly or potential problem is found, the corresponding scheduling strategy can be quickly matched and executed. This real-time monitoring and rapid response mechanism helps to reduce fault recovery time and reduce the risk of business interruption caused by network problems.

[0090] Preferably, the real-time evaluation of the adjusted network performance, if the performance does not meet the preset standard, continues to optimize the scheduling strategy until the performance requirement is met, specifically includes:

[0091] Use network monitoring tools to collect adjusted network performance data in real time;

[0092] Analyze the collected data in real time and calculate the current network performance index value;

[0093] Compare the calculated performance index values ​​with the preset standards to determine whether the network performance meets the standards. If all performance indicators meet or exceed the preset standards, the current network performance is considered good and no further adjustment is required. Otherwise, analyze the shortcomings of the current scheduling strategy and identify the key factors that lead to substandard performance.

[0094] According to the analysis results, the scheduling strategy is adjusted accordingly;

[0095] The further adjusted scheduling strategy is deployed to network devices and control systems.

[0096] In this embodiment, a closed-loop optimization mechanism is established. By collecting and analyzing network performance data in real time and comparing it with preset standards, problems with network performance that do not meet standards are discovered in a timely manner. On this basis, by further analyzing the deficiencies of the scheduling strategy and adjusting the scheduling strategy accordingly, a process of continuous iteration and continuous optimization is formed. This closed-loop optimization mechanism ensures that network performance can continue to meet business needs and continue to improve. In the process of real-time evaluation and adjustment of network performance, the network performance indicator value is always compared with the preset standard to ensure that the network performance reaches or exceeds the expected level. This strict standard control mechanism helps to avoid problems caused by network performance not meeting standards. It can prevent business interruptions or performance degradation caused by unsatisfactory network performance, thereby ensuring the stability and reliability of the network. When it is found that the network performance does not meet the standards, the technical solution deeply analyzes the shortcomings of the current scheduling strategy and identifies the key factors that lead to the substandard performance. This accurate problem identification capability helps to quickly locate the root cause of the problem, avoid detours or blind adjustments during the optimization process, and improve the optimization efficiency. The scheduling strategy is adjusted accordingly according to the analysis results, and the further adjusted scheduling strategy is deployed to the network equipment and control system. This dynamic adjustment capability enables the network management system to quickly respond to changes in the network environment and changes in business needs, ensuring that the network performance is always maintained in the optimal state.

[0097] A dynamic traffic scheduling system based on SD-WAN technology, comprising:

[0098] Real-time monitoring module, used to monitor the performance parameters of each link and node in the SD-WAN network in real time;

[0099] The traffic pattern analysis module is connected to the real-time monitoring module, and is used to receive the monitored performance parameters and analyze the network traffic pattern using a preset algorithm to identify high-traffic periods, low-traffic periods, and key business traffic;

[0100] A policy adjustment module, connected to the traffic pattern analysis module, for dynamically adjusting network routing and bandwidth allocation policies based on the results of the traffic pattern analysis module;

[0101] A performance evaluation module, connected to the policy adjustment module, for evaluating the adjusted network performance in real time;

[0102] The scheduling optimization module is connected to the performance evaluation module. When the performance evaluation module determines that the network performance does not meet the preset standard, the scheduling optimization module is triggered to continue optimizing the scheduling strategy until the performance requirements are met.

[0103] Preferably, the system further comprises:

[0104] The logging module is used to record the network status, scheduling strategy and performance evaluation results before and after the adjustment.

[0105] A computing device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned dynamic traffic scheduling method based on SD-WAN technology are implemented.

[0106] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-mentioned dynamic traffic scheduling method based on SD-WAN technology.

[0107] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A dynamic traffic scheduling method based on SD-WAN technology, characterized in that: Specifically include: Real-time monitoring of the performance parameters of each link and node in the SD-WAN network; Based on the monitored performance parameters, the preset algorithm is used to analyze the network traffic pattern to identify high-traffic periods, low-traffic periods and key business traffic; Dynamically adjust network routing and bandwidth allocation strategies based on traffic pattern analysis results; Evaluate the adjusted network performance in real time. If the performance does not meet the preset standard, continue to optimize the scheduling strategy until the performance requirements are met. The network status, scheduling strategy and performance evaluation results before and after the adjustment are recorded in the log.

2. According to the SD-WAN technology-based dynamic traffic scheduling method of claim 1, it is characterized in that: The real-time monitoring of the performance parameters of each link and node in the SD-WAN network specifically includes: Deploy monitoring probes on key nodes and links of the SD-WAN network; The key performance parameters of each link and node are collected in real time based on monitoring probes, including bandwidth utilization, delay, jitter, packet loss rate and error rate; For key business traffic, DPI technology is used to conduct in-depth analysis of key performance parameters to identify application type information and user behavior information; The collected key performance parameters are integrated with the application type information and user behavior information identified by DPI technology to form performance parameters for each link and node.

3. According to claim 2, a dynamic traffic scheduling method based on SD-WAN technology is characterized in that: The method uses a preset algorithm to analyze network traffic patterns based on the monitored performance parameters to identify high-traffic periods, low-traffic periods, and key business traffic, including: Extract traffic pattern features based on the monitored performance parameters to obtain traffic statistical features, traffic trend features, and traffic periodicity features; Use time series analysis algorithms to predict traffic statistics, traffic trends, and traffic periodicity to identify future high and low traffic periods; By combining the application type information and user behavior information identified by DPI technology, as well as statistical characteristics, trend characteristics, and periodic characteristics, key business traffic can be identified.

4. The dynamic traffic scheduling method based on SD-WAN technology according to claim 3 is characterized in that: The flow pattern feature extraction is performed based on the monitored performance parameters to obtain flow statistical features, flow trend features and flow periodic features, specifically including: Calculate the average bandwidth utilization, peak bandwidth, total traffic, and packet loss rate in each time window to obtain traffic statistics characteristics; Using the sliding window method, the trend of traffic changes is calculated, the upward or downward trend is identified, and the traffic trend characteristics are obtained; The periodic patterns in the flow data are identified by Fourier transform, and the periodic characteristics of the flow are obtained.

5. The dynamic traffic scheduling method based on SD-WAN technology according to claim 4 is characterized in that: The method of dynamically adjusting network routing and bandwidth allocation strategies based on traffic pattern analysis results specifically includes: Formulate a scheduling strategy, wherein the scheduling strategy includes a bandwidth reservation strategy, a routing optimization strategy, and a load balancing strategy; Deploy the developed scheduling strategy to network devices and control systems; Network equipment and control systems continuously monitor key performance parameters and match corresponding scheduling strategies based on the analysis results of high-traffic periods, low-traffic periods and key business traffic. Dynamically adjust network routing and bandwidth allocation strategies based on the matching scheduling strategy.

6. The dynamic traffic scheduling method based on SD-WAN technology according to claim 5 is characterized in that: The real-time evaluation of the adjusted network performance, if the performance does not meet the preset standard, continues to optimize the scheduling strategy until the performance requirements are met, specifically including: Use network monitoring tools to collect adjusted network performance data in real time; Analyze the collected data in real time and calculate the current network performance index value; Compare the calculated performance index values ​​with the preset standards to determine whether the network performance meets the standards. If all performance indicators meet or exceed the preset standards, the current network performance is considered good and no further adjustment is required. Otherwise, analyze the shortcomings of the current scheduling strategy and identify the key factors that lead to substandard performance. According to the analysis results, the scheduling strategy is adjusted accordingly; The further adjusted scheduling strategy is deployed to network devices and control systems.

7. A dynamic traffic scheduling system based on SD-WAN technology, characterized in that: include: Real-time monitoring module, used to monitor the performance parameters of each link and node in the SD-WAN network in real time; The traffic pattern analysis module is connected to the real-time monitoring module, and is used to receive the monitored performance parameters and analyze the network traffic pattern using a preset algorithm to identify high-traffic periods, low-traffic periods, and key business traffic; A policy adjustment module, connected to the traffic pattern analysis module, for dynamically adjusting network routing and bandwidth allocation policies based on the results of the traffic pattern analysis module; A performance evaluation module, connected to the policy adjustment module, for evaluating the adjusted network performance in real time; The scheduling optimization module is connected to the performance evaluation module. When the performance evaluation module determines that the network performance does not meet the preset standard, the scheduling optimization module is triggered to continue optimizing the scheduling strategy until the performance requirements are met.

8. The dynamic traffic scheduling system based on SD-WAN technology according to claim 7 is characterized in that: The system further comprises: The logging module is used to record the network status, scheduling strategy and performance evaluation results before and after the adjustment.

9. A computing device, characterized in that It includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the dynamic traffic scheduling method based on SD-WAN technology described in any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, which, when executed by a processor, implements the steps of the dynamic traffic scheduling method based on SD-WAN technology as described in any one of claims 1 to 6.

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