A smart routing scheduling method and related equipment

Abstract

This invention discloses an intelligent routing scheduling method and related equipment. The method includes: periodically collecting link quality data for each link of a target terminal and storing it in a link quality database; quantifying the quality score of each link based on historical and real-time data; integrating and transforming these scores to obtain the link quality scores for each link; and updating the routing table based on the link quality scores. If the transmission links in the routing table change, a smoothing strategy is used to switch the data transmission route for the target terminal. This invention, by periodically collecting and storing the quality data of each link and combining it with historical data for comprehensive evaluation, can comprehensively and accurately quantify the transmission quality of links. This effectively solves the problem of the simplistic approach of traditional solutions that rely solely on connectivity status for routing, and can be widely applied in the field of data processing technology.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to an intelligent routing and scheduling method and related equipment. Background Technology

[0002] With the widespread adoption of smart devices, a single router typically integrates multiple internet access links, such as wired network ports (Ethernet), 2.4GHz Wi-Fi, 5GHz Wi-Fi, and even faster Wi-Fi 6 / 7. However, routers using traditional routing mechanisms lack the ability to comprehensively evaluate and optimize link quality, and they usually assign data transmission paths to terminals using default routes or random routing.

[0003] Specifically, existing technical solutions mostly remain at the link connectivity detection level, meaning that link switching is only triggered when the application's link is physically disconnected or completely unable to communicate (i.e., passive response). This passive response scheduling mechanism has the following technical drawbacks: Single routing criterion: Decisions are made solely based on the link's connectivity status, failing to perceive the link's real-time transmission quality; Lack of foresight: Adjustments are only made after link quality deterioration has already affected user experience, lacking the initiative to proactively avoid link transmission risks; Crude switching mechanism: When link switching is needed, the original link is usually directly interrupted and the connection rebuilt, easily leading to data packet loss, service lag, or even connection interruption, impacting the user experience. Summary of the Invention

[0004] The main objective of this invention is to propose an intelligent routing scheduling method, device, electronic device, storage medium, and program product, aiming to overcome the shortcomings of existing multi-link routing scheduling, such as reliance on on / off status, passive switching, poor service adaptability, and easy interruption of transmission during routing switching, and to provide an intelligent routing scheduling scheme based on multi-dimensional quality scoring and dynamic smooth switching.

[0005] To achieve the above objectives, one aspect of this invention proposes an intelligent routing scheduling method, the method comprising: Based on a preset collection period, the link quality data of each link of the target terminal is periodically collected and stored in the link quality database; the link quality data includes multiple link quality indicators. Based on historical and real-time data in the link quality database, the quality score of each link quality indicator is quantified. The quality scores of all metrics for each link are integrated and transformed into a link quality score for each link. The routing table is then updated based on the link quality scores. If the transmission link in the routing table changes, the data transmission route to the target terminal is switched using a smoothing strategy. Then, the process returns to the step of quantifying the quality score of each link quality indicator based on historical and real-time data in the link quality database, and continues to schedule the route to the target terminal.

[0006] In some embodiments, the method further includes the following steps: Obtain the access scenario of the target terminal; The collection cycle is configured based on the access scenario mapping.

[0007] In some embodiments, link quality metrics include latency, packet loss rate, and bandwidth, and the metric quality score includes bandwidth score, latency score, and packet loss rate score. Based on historical and real-time data in the link quality database, the metric quality score for each link quality metric is quantified, including the following steps: A bandwidth score is obtained by quantifying the ratio of current bandwidth in real-time data to peak bandwidth in historical data through a score conversion process. Based on latency and packet loss rate in real-time data, latency score and packet loss rate score are obtained by quantifying them using a segmented interval method.

[0008] In some embodiments, the quality scores of all metrics for each link are integrated and transformed into a link quality score for each link, including the following steps: Obtain the service characteristics of the target terminal, determine the service type based on the service characteristics using preset service classification rules, and obtain the indicator weight of each link quality indicator by looking up a preset mapping table according to the service type. And / or, in response to a configuration trigger command, update the weight of each link quality metric; The configuration trigger commands include manual trigger commands and conditional trigger commands; The link quality score is obtained by weighting and summing the quality scores of all indicators for the same link based on the indicator weights.

[0009] In some embodiments, updating the routing table based on link quality scores includes the following steps: Obtain the transmission link originally marked in the routing table; If the link quality score of the transmission link is lower than the preset score threshold, or if there is a link whose link quality score is higher than the link quality score of the transmission link, a routing table update operation is triggered. In response to a routing table update operation, the transmission links in the routing table are updated based on the link with the highest link quality score.

[0010] In some embodiments, updating the routing table based on link quality scores further includes the following steps: In response to a routing table update operation, a verification window is generated. If the link quality score of the transmission link originally marked in the routing table rebounds to the preset qualified range within the verification window, the transmission link in the routing table will not be updated.

[0011] In some embodiments, data transmission routing is switched for the target terminal using a smoothing strategy, including the following steps: The transmission link before the change in the routing table is used as the first link, and the transmission link after the change in the routing table is used as the second link. A preset proportion of traffic from the first link to the second link is switched to the traffic of the service being processed by the target terminal, triggering the generation of a monitoring window period; If no abnormality occurs in the data transmission of the second link within the monitoring window period, the traffic of the first link will be gradually switched to the second link based on the preset traffic increase step size until all traffic of the business processed by the target terminal is switched from the first link to the second link. If a data transmission anomaly occurs on the second link during the monitoring window, a preset proportion of traffic will be switched back to the first link, terminating the data transmission route switching. Data transmission anomalies include excessive latency and excessive packet loss.

[0012] In some embodiments, the method further includes the following steps: Based on the update frequency limiting mechanism, data transmission route switching is limited by a preset window time. Within the preset window period, only one route switch is allowed.

[0013] To achieve the above objectives, another aspect of the present invention provides an intelligent routing scheduling device, the device comprising: The first module is used to periodically collect link quality data of each link of the target terminal and store it in the link quality database based on a preset collection period; the link quality data includes multiple link quality indicators. The second module is used to quantify the quality score of each link quality indicator based on historical and real-time data in the link quality database. The third module is used to integrate all quality scores of each link, convert them into link quality scores for each link, and update the routing table based on the link quality scores. The fourth module is used to switch the data transmission route to the target terminal through a smoothing strategy if the transmission link in the routing table changes, and then return to the operation of the second module to continue the routing scheduling of the target terminal.

[0014] In some embodiments, the apparatus further includes a fifth module for performing the following operations: Obtain the access scenario of the target terminal; The collection cycle is configured based on the access scenario mapping.

[0015] In some embodiments, the apparatus further includes a sixth module for performing the following operations: Based on the update frequency limiting mechanism, data transmission route switching is limited by a preset window time. Within the preset window period, only one route switch is allowed.

[0016] To achieve the above objectives, another aspect of the present invention provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the aforementioned method.

[0017] To achieve the above objectives, another aspect of the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned method.

[0018] To achieve the above objectives, another aspect of the present invention provides a computer program product, including a computer program that, when executed by a processor, implements the aforementioned method.

[0019] The embodiments of the present invention include at least the following beneficial effects: The present invention provides an intelligent routing scheduling method, device, electronic device, storage medium, and program product. This solution periodically collects link quality data of each link of the target terminal and stores it in a link quality database based on a preset collection period. The link quality data includes multiple link quality indicators. Based on historical and real-time data in the link quality database, the indicator quality score of each link quality indicator is quantified. All indicator quality scores of each link are integrated and transformed into the link quality score of each link. The routing table is updated based on the link quality score. If the transmission link in the routing table changes, the data transmission route of the target terminal is switched through a smoothing strategy. The step of quantifying the indicator quality score of each link quality indicator based on historical and real-time data in the link quality database is returned to be executed, and the routing scheduling of the target terminal is continuously performed. This invention, through periodically collecting and storing quality data from each link and combining it with historical data for comprehensive evaluation, can fully and accurately quantify the transmission quality of the links, thus effectively solving the problem of the simplistic approach of traditional solutions that rely solely on connectivity status for routing. Secondly, through continuous quality scoring and dynamic routing table updates, this invention enables a shift from "passive response" to "proactive prediction," allowing for early route optimization when link quality trends change. Furthermore, by introducing a smoothing strategy, this invention effectively avoids data packet loss or service interruptions caused by sudden link changes, significantly improving data transmission stability and user experience in multi-link environments. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of an implementation environment for an intelligent routing scheduling method provided in an embodiment of the present invention; Figure 2 This is a flowchart illustrating an intelligent routing and scheduling method provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of an intelligent routing scheduling device provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of the electronic device provided in an embodiment of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this invention clearer, the 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 merely illustrative of the invention and are not intended to limit the invention. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of this invention; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this invention as detailed in the appended claims.

[0022] It is understood that the terms "first," "second," etc., used in this invention may be used to describe various concepts, but unless specifically stated otherwise, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of embodiments of this invention, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the words "if" or "when" as used herein may be interpreted as "when," "in response to determination," or "in the event of a determination."

[0023] The terms “at least one,” “multiple,” “each,” “any,” etc., used in this invention, “at least one” includes one, two, or more than two; “multiple” includes two or more than two; “each” refers to each of the corresponding multiple; and “any” refers to any one of the multiple.

[0024] Unless otherwise defined, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used in this invention is for descriptive purposes only and is not intended to limit the invention.

[0025] In related technologies, existing solutions mostly remain at the level of link connectivity detection, meaning that link switching is only triggered (i.e., passive response) when the application's link is physically disconnected or completely unable to communicate. This passive response scheduling mechanism suffers from technical defects such as a single routing criterion, a lack of foresight, and a crude switching mechanism.

[0026] In view of this, this invention provides an intelligent routing scheduling method and related equipment. This method periodically collects link quality data for each link of the target terminal and stores it in a link quality database based on a preset collection period. The link quality data includes multiple link quality indicators. Based on historical and real-time data in the link quality database, a quality score for each link quality indicator is quantified. All quality scores for each link are integrated and converted into a link quality score for each link. The routing table is updated based on the link quality scores. If the transmission link in the routing table changes, a smoothing strategy is used to switch the data transmission route for the target terminal. The process then returns to the step of quantifying the quality score for each link quality indicator based on historical and real-time data in the link quality database, continuously performing routing scheduling for the target terminal. This invention, through periodically collecting and storing quality data from each link and combining it with historical data for comprehensive evaluation, can fully and accurately quantify the transmission quality of the links, thus effectively solving the problem of the simplistic approach of traditional solutions that rely solely on connectivity status for routing. Secondly, through continuous quality scoring and dynamic routing table updates, this invention enables a shift from "passive response" to "proactive prediction," allowing for early route optimization when link quality trends change. Furthermore, by introducing a smoothing strategy, this invention effectively avoids data packet loss or service interruptions caused by sudden link changes, significantly improving data transmission stability and user experience in multi-link environments.

[0027] It is understood that the intelligent routing and scheduling method provided by this invention can be applied to any computer device with data processing and computing capabilities, and this computer device can be various terminals or servers. When the computer device in the embodiment is a server, the server is an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. Optionally, the terminal can be a smartphone, tablet computer, laptop computer, or desktop computer, but it is not limited to these.

[0028] like Figure 1The diagram shown is a schematic representation of an implementation environment provided by an embodiment of the present invention. (Refer to...) Figure 1 The implementation environment includes at least one terminal 102 and a server 101. The terminal 102 and the server 101 can be connected via a network, either wirelessly or via a wired connection, to complete data transmission and exchange.

[0029] Server 101 can be a standalone physical server, a server cluster or distributed system consisting of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.

[0030] Additionally, server 101 can also be a node server in a blockchain network. Blockchain is a novel application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms.

[0031] Terminal 102 can be a smartphone, tablet computer, laptop computer, desktop computer, smart speaker, smartwatch, etc., but is not limited to these. Terminal 102 and server 101 can be directly or indirectly connected via wired or wireless communication, and this embodiment of the invention does not impose any limitations.

[0032] For example, based on Figure 1 The implementation environment shown in this embodiment of the invention provides an intelligent routing scheduling method. The following description uses the application of this intelligent routing scheduling method in server 101 as an example. It can be understood that this intelligent routing scheduling method can also be applied to terminal 102.

[0033] Reference Figure 2 , Figure 2 This is an optional flowchart of an intelligent routing scheduling method provided in an embodiment of the present invention. The executing entity of the intelligent routing scheduling method can be any of the aforementioned computer devices (including servers or terminals). Figure 2 The method may include, but is not limited to, steps S100 to S400.

[0034] Step S100: Based on a preset collection period, periodically collect link quality data of each link of the target terminal and store it in the link quality database. The link quality data includes multiple link quality metrics. It should be noted that in some embodiments, the method further includes the following steps: obtaining the access scenario of the target terminal; and configuring the collection period based on the access scenario mapping.

[0035] For example, in some specific implementations, the access scenario of the target terminal can be obtained before starting to collect link data to configure the collection period. For instance, when the current environment is detected as a high-density terminal access scenario (such as a conference room or shopping mall), the collection period can be configured to a shorter 10ms in order to more sensitively capture link fluctuations; if the current scenario is detected as a normal home scenario, the collection period can be configured to a longer 100ms in order to balance collection accuracy and system resource consumption.

[0036] Step S200: Based on historical and real-time data in the link quality database, quantify the quality score of each link quality indicator. It should be noted that the link quality indicators include latency, packet loss rate, and bandwidth. The indicator quality score includes bandwidth score, latency score, and packet loss rate score. In some embodiments, step S200 may include the following steps: based on the ratio of the current bandwidth in real-time data to the peak bandwidth in historical data, a bandwidth score is obtained by conversion and quantification; based on the latency and packet loss rate in real-time data, a latency score and a packet loss rate score are obtained by segmentation and interval quantification.

[0037] For example, in some specific implementations, the steps for quantifying the quality score of indicators can be implemented as follows: Bandwidth score calculation: Based on the ratio of current bandwidth in real-time data to peak bandwidth in historical data, normalization is performed, i.e., Sb = (current bandwidth / peak bandwidth) * 100.

[0038] The latency score and packet loss rate score are quantified using a segmented interval mapping method: For example, the latency scoring rules are as follows: 100 points for latency ≤ 20ms, 80 points for 20ms < latency ≤ 50ms, 60 points for 50ms < latency ≤ 100ms, and 0 points for latency > 100ms; the packet loss rate scoring rules are as follows: 100 points for a packet loss rate of 0%, 80 points for 0% < packet loss rate ≤ 1%, 60 points for 1% < packet loss rate ≤ 5%, and 0 points for packet loss rate > 5%.

[0039] Step S300: Integrate all quality scores of each link and convert them into link quality scores for each link. Update the routing table based on the link quality scores. It should be noted that in some embodiments, integrating all quality scores of each link to obtain the link quality score for each link may include the following steps: obtaining the service characteristics of the target terminal, determining the service type based on the service characteristics through preset service division rules, obtaining the indicator weight of each link quality indicator by looking up a preset mapping table according to the service type; and / or, updating the indicator weight of each link quality indicator in response to a configuration trigger instruction; wherein, the configuration trigger instruction includes manual trigger instruction and conditional trigger instruction; and performing a weighted summation of all quality scores of the same link based on the indicator weight to obtain the link quality score of the corresponding link.

[0040] For example, in some specific implementations, when integrating the quality scores of various indicators into a link quality score, the service characteristics of the target terminal can be obtained first to determine the service type. For instance, the router identifies the service type through port number, 5-tuple, and service transmission characteristics (packet length, packet interval, and traffic duration), including low-latency priority services, high-bandwidth priority services, and general services. For example, a TCP packet with a destination port of 80 and a bandwidth of 443 is considered a webpage. Game service identification: if the average packet length is ≤128 bytes, the packet interval is stable between 10ms and 50ms, the uplink and downlink traffic ratio is relatively balanced between 0.5 and 2, and the connection duration is >5 seconds, then it is determined to be a game service. If the average packet length is ≥512 bytes, the downlink to uplink ratio is ≥10, the downlink traffic is ≥1MB per second, and the transmission protocol is TCP, then it is determined to be a download service. If HTTP / HTTPS Content-Disposition: attachment, FTP protocol, or BT / Thunder characteristic ports (such as 6881-6889) are detected, it can be directly determined to be a download service (as an auxiliary identification, not relied upon). Subsequently, the router can look up the corresponding indicator weights (latency weight, bandwidth weight, and packet loss rate weight) according to the preset mapping table.

[0041] In addition, users can manually adjust the weights through the management interface. For example, to increase the bandwidth weight to meet the needs of video services, the router will respond to this manual configuration trigger command and update the corresponding indicator weights. At the same time, the weights can be dynamically adjusted according to the link conditions. For example, when the latency is relatively long (greater than 50ms), the latency weight can be dynamically increased and the weights of other indicators can be decreased accordingly.

[0042] Finally, based on the updated weights, the router performs a weighted sum of the scores for each link metric to calculate the final link quality score.

[0043] It should be noted that, in some embodiments, updating the routing table based on link quality scores may include the following steps: obtaining the transmission links originally marked in the routing table; if the link quality score of the transmission link is lower than a preset score threshold, or if there is a link whose link quality score is greater than the link quality score of the transmission link, triggering a routing table update operation; in response to the routing table update operation, updating the transmission links in the routing table based on the link with the highest link quality score.

[0044] For example, in some specific implementations, the process of updating the routing table can be implemented as follows: The router obtains the transmission links originally marked in the current routing table (e.g., the currently used Wi-Fi link); if the calculation finds that the current link quality score of the Wi-Fi link is lower than a preset threshold of 70 points, or if the 85-point score of another wired link is found to be higher than the 82-point score of the current Wi-Fi link, the router determines that the update conditions are met and triggers the routing table update operation; in response to this operation, the router updates the transmission link in the routing table from the Wi-Fi link to the link with the highest current quality score (e.g., the wired link).

[0045] It should be noted that, in some embodiments, updating the routing table based on the link quality score may also include the following steps: in response to the routing table update operation, triggering the generation of a verification window period; if the link quality score of the transmission link originally marked in the routing table bounces back to the preset qualified range within the verification window period, the transmission link in the routing table is not updated.

[0046] For example, in some specific implementations, to prevent frequent route switching caused by brief fluctuations in link quality, when a routing table update operation is triggered, the router does not immediately perform the update. Instead, it first generates a 500ms verification window. During this window, the router continuously monitors the scores of the original Wi-Fi link and candidate wired links. If, within 500ms, the Wi-Fi link score rebounds from below 70 points to 80 points (i.e., reaches the acceptable range and recovers to a satisfactory state), the router determines that the trigger was a momentary fluctuation and abandons the routing table update operation.

[0047] Step S400: If the transmission link in the routing table changes, the data transmission route of the target terminal is switched through a smoothing strategy. Then, the step of quantifying the quality score of each link quality indicator based on historical and real-time data in the link quality database is returned to continue the routing scheduling of the target terminal. It should be noted that in some embodiments, the data transmission route switching of the target terminal through a smoothing strategy may include the following steps: using the transmission link before the change in the routing table as the first link and the transmission link after the change in the routing table as the second link; switching a preset proportion of the traffic of the service processed by the target terminal from the first link to the second link, triggering the generation of a monitoring window period; if the data transmission of the second link does not experience any abnormalities within the monitoring window period, gradually switching the traffic of the first link to the second link based on a preset traffic increment step, until all the traffic of the service processed by the target terminal is switched from the first link to the second link; if the second link experiences a data transmission abnormality within the monitoring window period, switching a preset proportion of the traffic back from the second link to the first link, terminating the data transmission route switching; wherein, the data transmission abnormality includes latency exceeding the standard and packet loss rate exceeding the standard.

[0048] For example, in some specific implementations, the smoothing strategy can be implemented as follows: First, the first link before the change (such as the original Wi-Fi link) and the second link after the change (such as the wired link) are marked in the routing table; then, the router switches 10% of the traffic of the service processed by the target terminal from the first link to the second link and enters a 50ms monitoring window period; if there is no delay or packet loss abnormality in the data transmission of the second link during the monitoring window period, the router gradually and smoothly switches the remaining traffic from the first link to the second link according to a preset traffic increase step size (for example, increasing the traffic by 18% every 10ms) until all traffic is transmitted through the second link; if an anomaly such as a sudden increase in packet loss rate occurs on the second link during the monitoring window period, the router immediately switches the switched 10% traffic back to the first link and terminates the current routing switch process.

[0049] It should be noted that in some embodiments, the method may further include the following steps: based on the update frequency limiting mechanism, limiting data transmission route switching by a preset window time; wherein, only one route switching is allowed to be performed within the preset window time.

[0050] For example, in some specific implementations, jitter can also be avoided by limiting the frequency of routing table updates (such as allowing only one switch within 5 seconds for the same service).

[0051] To explain in detail the principle of the technical solution of the present invention, the overall process of the present invention will be described below with reference to some specific embodiments. It is easy to understand that the following is an explanation of the technical principle of the present invention and should not be regarded as a limitation of the present invention.

[0052] First, it should be noted that in existing technologies, when a router has multiple internet access pathways such as a network port, 2.4G Wi-Fi, and 5G Wi-Fi, if none of the links are broken, it will not determine which link is optimal to use, and will usually randomly select a link for internet access.

[0053] Therefore, this invention provides an intelligent routing scheduling method. When a terminal has multiple links (such as a physical network card connection, Wi-Fi, etc.) to access the internet through a router, the optimal link can be determined based on multi-dimensional detection of latency, bandwidth, packet loss rate, etc., and then the optimal link is used for the user. Specifically, the intelligent routing scheduling method of this invention can be implemented through the following steps: (1) Link parameter collection: Real-time bandwidth, transmission latency, and packet loss rate of each link are collected every 10-100ms and stored in the link quality database. The collection period can be adjusted according to the needs of the scenario. A short period of 10-30ms can be used in high-density terminal access scenarios, and a long period of 50-100ms can be used in ordinary home scenarios, taking into account both collection accuracy and resource consumption. For example, the collection period can be set to 30ms to collect the bandwidth, transmission latency, and packet loss rate of wired links, Wi-Fi 6 2.4G links, and Wi-Fi 6 5G links in real time and store them in the link quality database to continuously accumulate historical data. (2) Link Quality Prediction: By combining historical and real-time data from the link quality database, the weights of three dimensions—transmission delay, packet loss rate, and bandwidth stability—are calculated to obtain a quality score for each link within the next 1-5 seconds. The quality score is calculated by weighting bandwidth weight, delay weight, and packet loss rate weight. The bandwidth weight, delay weight, and packet loss rate weight can be dynamically adjusted according to user needs. For example, in industrial control scenarios where delay is critical, the delay weight can be increased; in video transmission scenarios where bandwidth is critical, the bandwidth weight can be increased. This solution does not rely on a special network architecture and can be directly deployed on ordinary routers. Through the fusion training of historical and real-time data, accurate prediction of link quality can be achieved, thus mitigating transmission risks caused by sudden changes in link quality. For example, setting the bandwidth weight to 0.4, the delay weight to 0.4, and the packet loss rate weight to 0.2, the quality score range is 0-100 points. A score ≥80 is considered a high-quality link, 60-79 is a qualified link, and <60 is a poor-quality link. The weights are not fixed; they can be categorized and defined according to business needs, or allocated by users based on the actual importance of their business. The weights are dynamic and can be adjusted based on link conditions. For example, when latency is high (greater than 50ms), the latency weight can be dynamically increased. Bandwidth stability refers to the fluctuation of bandwidth sample values ​​per unit time, which can be calculated by measuring the variance or standard deviation of the sample values. Quality scoring is not just a weighted evaluation; it must also be normalized, standardizing values ​​from different units to 0-100.

[0054] Specifically, the scoring formula is as follows: Score = Wb*Sb + Wd*Sd + Wl*Sl Where Wb represents bandwidth weight, Wd represents latency weight, and Wl represents packet loss rate weight. Bandwidth score Sb = Current bandwidth / Peak bandwidth * 100; The latency score Sd and packet loss rate score Sl are scored using a segmented interval method, for example: A delay of ≤20ms scores 100 points, 20ms < delay ≤50ms scores 80 points, 50ms < delay ≤100ms scores 60 points, and a delay >100ms scores 0 points. A packet loss rate of 0% earns 100 points, 0% < packet loss rate ≤ 1% earns 80 points, 1% < packet loss rate ≤ 5% earns 60 points, and a packet loss rate > 5% earns 0 points.

[0055] In addition, service weights need to be categorized according to service type: the services accessed by the router are divided into three categories, with different preset weight allocation benchmarks: ① Low-latency priority services (such as games and industrial control commands): latency weight 0.5, bandwidth weight 0.3, packet loss rate weight 0.2, prioritize low latency to avoid lag.

[0056] ② High-bandwidth priority services (such as video playback and file download): bandwidth weight 0.5, latency weight 0.2, packet loss rate weight 0.3, prioritize high bandwidth to improve transmission rate.

[0057] ③ General services (such as web browsing and instant messaging): bandwidth weight 0.3, latency weight 0.3, packet loss rate weight 0.4, taking into account the balance of the three.

[0058] It should be noted that routers can identify service types through port numbers, 5-tuples, and service transmission characteristics (packet length, packet interval, and traffic duration), including low-latency priority services, high-bandwidth priority services, and general services. For example, a TCP packet with a destination port of 80 and 443 is considered a webpage. Game service identification: If the average packet length is ≤128 bytes, the packet interval is stable between 10ms and 50ms, the upstream and downstream traffic ratio is relatively balanced between 0.5 and 2, and the connection duration is >5 seconds, then it is determined to be a game service. If the average packet length is ≥512 bytes, the downstream to upstream traffic ratio is ≥10, the downstream traffic within 1 second is ≥1MB, and the transmission protocol is TCP, then it is determined to be a download service. If HTTP / HTTPS Content-Disposition: attachment (attachment download), FTP protocol, or BT / Thunder characteristic ports (such as 6881-6889) are identified, it can be directly determined to be a download service (as an auxiliary identification method, not relied upon).

[0059] When multiple services are simultaneously available on the same terminal, the router sets a protection threshold for core services (low latency priority) on a terminal-by-terminal basis. For example, if the measured latency of gaming / industrial control services is ≤20ms and the packet loss rate is ≤1%, then downloading / video services can use bandwidth normally. If the latency of core services is >20ms or the packet loss rate is >1%, then the bandwidth of downloading / video services will be automatically limited (reduced to 50% of the original rate) until the core service indicators return to within the threshold. General services always use the remaining bandwidth and do not preempt core service resources.

[0060] (3) Routing table update: When the quality score of a link is lower than the preset threshold, or when there is a backup link with a higher quality score, the routing table is dynamically updated, and the link with the highest quality score is selected for data transmission first. For example, if the preset quality score threshold is 70 points, when the score of a link is lower than 70 points, or when there is a backup link with a higher score, the routing table is updated. For example, if the Wi-Fi 6 5G link score drops to 65 points due to too many terminal accesses, while the wired link score is 85 points, the data transmission route will be switched to the wired link. If the scores of the Wi-Fi 6 5G link and the wired link are both 82 points, the wired link with lower latency will be selected first. If the quality scores of multiple links are close, the link with lower latency will be selected first to avoid transmission interruption or lag due to sudden changes in link quality. This step, through a "predictive update trigger" mechanism, differs from the passive response mode of existing technologies that "trigger updates only after link quality deteriorates." It allows for advance preparation for route switching, minimizing switching latency. Simultaneously, the latency-priority fallback strategy addresses the issue of existing intelligent routing algorithms tending to favor a single bandwidth metric and sacrificing real-time service transmission experience, achieving an optimal balance between latency and bandwidth. Specifically, it can be considered that switching will not be performed if the score difference is within 5 points.

[0061] (4) Add a route update debouncing mechanism: After triggering the update, first perform a "verification window" (e.g., 500ms) to confirm that the link score degradation / optimization status continues before executing the update; Limit the frequency of routing table updates (allow only one switch within 5 seconds for the same service) to avoid jitter.

[0062] Specifically, route update debouncing (verification window period): When the link quality score triggers the route update condition (such as high quality → low quality, low quality → high quality), the router does not immediately perform the route update, but enters a "verification window" (such as 500ms). During the verification window, the router only continuously collects latency, packet loss rate, and bandwidth stability data for the link, without adjusting the traffic forwarding path of the current service or affecting the transmission of existing services. If the link score continuously meets the update conditions during the verification window (e.g., the current link score is always <60 points within 500ms, or the better link score is always ≥80 points), the link status is considered stable, and the route switching process is triggered; if the status recovers during the window (e.g., the score bounces back to the acceptable range), the route update is abandoned to avoid jitter.

[0063] (5) Smooth routing strategy: After triggering the switchover, first divert 10% of traffic to the new link to verify normal transmission (no abnormalities in latency / packet loss); then gradually increase the traffic to 100% within 50ms. Specifically, the routing handover smoothing strategy only initiates the smooth handover process on the router after the verification window period has passed: The first step is to switch 10% of the traffic of this service to the new link and continuously monitor the transmission indicators of the new link (latency ≤ threshold, packet loss rate ≤ threshold). The second step is to gradually increase the traffic to 100% if there are no abnormalities in the new link transmission within 50ms (e.g., increase by 18% every 10ms); if there is an abnormality in the new link, immediately switch 10% of the traffic back to the original link, terminate the switch and record the abnormality.

[0064] It should be noted that an update frequency limit can also be set: the routing table update frequency for the same service is limited to only one switch within 5 seconds. Even if the verification window is triggered multiple times, a 5-second cooldown period must be waited before the next switch is executed, further avoiding link jitter.

[0065] In summary, this invention breaks through the limitations of existing intelligent routing algorithms. By combining a dynamic weighted link quality scoring mechanism, it solves the core pain points of existing technologies, such as "only being able to respond in real time and unable to avoid link risks in advance" and "fixed weights and inability to adapt to differentiated services." The technical solution of this invention can be directly deployed on ordinary routers without special architecture support, significantly improving deployment flexibility and versatility. It achieves optimal routing selection with both latency and bandwidth objectives, effectively avoiding the degradation of transmission experience caused by a single indicator.

[0066] like Figure 3 As shown, this embodiment of the invention also provides an intelligent routing scheduling device 900, which can implement the above-described method. This device may include: The first module 901 is used to periodically collect link quality data of each link of the target terminal and store it in the link quality database based on a preset collection period; wherein, the link quality data includes multiple link quality indicators. The second module 902 is used to quantify the quality score of each link quality indicator based on historical and real-time data in the link quality database. The third module 903 is used to integrate all quality scores of each link, convert them into link quality scores for each link, and update the routing table based on the link quality scores. The fourth module 904 is used to switch the data transmission route to the target terminal through a smoothing strategy if the transmission link in the routing table changes, and then return to execute the operation of the second module to continue the routing scheduling of the target terminal.

[0067] In some embodiments, the apparatus further includes a fifth module for performing the following operations: Obtain the access scenario of the target terminal; The collection cycle is configured based on the access scenario mapping.

[0068] In some embodiments, the apparatus further includes a sixth module for performing the following operations: Based on the update frequency limiting mechanism, data transmission route switching is limited by a preset window time. Within the preset window period, only one route switch is allowed.

[0069] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0070] This invention also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the method described above. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0071] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0072] like Figure 4 As shown, Figure 4 The hardware structure of an electronic device 1000 according to another embodiment is illustrated. The electronic device 1000 includes: The processor 1001 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (aSIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present invention. The memory 1002 can be implemented as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RaM). The memory 1002 can store the operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 1002 and is called and executed by the processor 1001. Input / output interface 1003 is used to implement information input and output; The communication interface 1004 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 1005 transmits information between various components of the device (e.g., processor 1001, memory 1002, input / output interface 1003, and communication interface 1004); The processor 1001, memory 1002, input / output interface 1003 and communication interface 1004 are connected to each other within the device via bus 1005.

[0073] The electronic device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0074] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0075] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0076] This invention also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0077] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0078] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0079] This invention provides an intelligent routing scheduling method, device, electronic device, storage medium, and program product. It periodically collects link quality data for each link of a target terminal and stores it in a link quality database based on a preset collection period. The link quality data includes multiple link quality indicators. Based on historical and real-time data in the link quality database, a quality score for each link quality indicator is quantified. All quality scores for each link are integrated and converted into a link quality score for each link. The routing table is updated based on these scores. If the transmission link in the routing table changes, a smoothing strategy is used to switch the data transmission route for the target terminal. The process then returns to the previous step of quantifying the quality score for each link quality indicator based on historical and real-time data in the link quality database, continuously performing routing scheduling for the target terminal. This invention, through periodically collecting and storing quality data from each link and combining it with historical data for comprehensive evaluation, can fully and accurately quantify the transmission quality of the links, thus effectively solving the problem of the simplistic approach of traditional solutions that rely solely on connectivity status for routing. Secondly, through continuous quality scoring and dynamic routing table updates, this invention enables a shift from "passive response" to "proactive prediction," allowing for early route optimization when link quality trends change. Furthermore, by introducing a smoothing strategy, this invention effectively avoids data packet loss or service interruptions caused by sudden link changes, significantly improving data transmission stability and user experience in multi-link environments.

[0080] The embodiments described in this invention are for the purpose of more clearly illustrating the technical solutions of the embodiments of this invention, and do not constitute a limitation on the technical solutions provided by the embodiments of this invention. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this invention are also applicable to similar technical problems.

[0081] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present invention, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0082] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0083] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0084] The preferred embodiments of the present invention have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present invention. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and spirit of the present invention should be within the scope of the claims of the present invention.

Claims

1. An intelligent routing scheduling method, characterized in that, The method includes the following steps: Based on a preset collection period, the link quality data of each link of the target terminal is periodically collected and stored in the link quality database; wherein, the link quality data includes multiple link quality indicators; Based on historical and real-time data in the link quality database, the quality score of each link quality indicator is quantified. The quality scores of all the aforementioned metrics for each link are integrated and transformed into a link quality score for each link. The routing table is then updated based on the link quality scores. If the transmission link in the routing table changes, the data transmission route for the target terminal is switched using a smoothing strategy. Then, the step of quantifying the quality score of each link quality indicator based on historical and real-time data in the link quality database is returned, and the routing scheduling for the target terminal continues.

2. The method according to claim 1, characterized in that, The method further includes the following steps: Obtain the access scenario of the target terminal; The collection period is configured based on the access scenario mapping.

3. The method according to claim 1, characterized in that, The link quality metrics include latency, packet loss rate, and bandwidth. The metric quality scores include bandwidth score, latency score, and packet loss rate score. The process of quantifying the metric quality score for each link quality metric based on historical and real-time data in the link quality database includes the following steps: A bandwidth score is obtained by quantifying the ratio of the current bandwidth in the real-time data to the peak bandwidth in the historical data of the same link through a score conversion. Based on the latency and packet loss rate in the real-time data, latency scores and packet loss rate scores are obtained by quantifying them using a segmented interval method.

4. The method according to claim 1, characterized in that, The process of integrating all the quality scores of each link to obtain a link quality score includes the following steps: The service characteristics of the target terminal are obtained, and the service type is determined based on the service characteristics through a preset service division rule. The weight of each link quality indicator is obtained by looking up a preset mapping table according to the service type. And / or, in response to a configuration trigger command, update the weight of each of the link quality metrics; The configuration triggering instructions include manual triggering instructions and conditional triggering instructions; The link quality score of the corresponding link is obtained by weighted summation of the quality scores of all the indicators for the same link based on the indicator weights.

5. The method according to claim 1, characterized in that, The process of updating the routing table based on the link quality score includes the following steps: Obtain the transmission link originally marked in the routing table; If the link quality score of the transmission link is lower than a preset score threshold, or if there is a link whose link quality score is higher than the link quality score of the transmission link, a routing table update operation is triggered. In response to the routing table update operation, the transmission link in the routing table is updated based on the link with the highest link quality score.

6. The method according to claim 5, characterized in that, The step of updating the routing table based on the link quality score further includes the following steps: In response to the routing table update operation, a verification window is generated. If the link quality score of the transmission link originally marked in the routing table rebounds to the preset qualified range within the verification window period, the transmission link in the routing table will not be updated.

7. The method according to claim 1, characterized in that, The step of switching the data transmission route for the target terminal using a smoothing strategy includes the following steps: The transmission link before the change in the routing table is taken as the first link, and the transmission link after the change in the routing table is taken as the second link; A preset proportion of traffic from the first link to the second link is switched to the traffic of the service being processed by the target terminal, triggering the generation of a monitoring window period; If no abnormality occurs in the data transmission of the second link during the monitoring window period, the traffic of the first link is gradually switched to the second link based on the preset traffic increase step size until all traffic of the service processed by the target terminal is switched from the first link to the second link; If a data transmission anomaly occurs on the second link during the monitoring window period, the preset proportion of traffic will be switched back from the second link to the first link, terminating the data transmission route switching; wherein, the data transmission anomaly includes excessive latency and excessive packet loss rate.

8. The method according to claim 1, characterized in that, The method further includes the following steps: Based on the update frequency limiting mechanism, the data transmission route switching is limited by a preset window time; Within the preset window period, only one route switch is allowed.

9. An intelligent routing scheduling device, characterized in that, The device includes: The first module is used to periodically collect link quality data of each link of the target terminal and store it in the link quality database based on a preset collection period; wherein, the link quality data includes multiple link quality indicators; The second module is used to quantify and obtain the quality score of each link quality indicator based on historical and real-time data in the link quality database. The third module is used to integrate all the quality scores of the indicators for each link, convert them into the link quality score of each link, and update the routing table based on the link quality score; The fourth module is used to switch the data transmission route of the target terminal through a smoothing strategy if the transmission link of the routing table changes, and then return to the operation of the second module to continue the routing scheduling of the target terminal.

10. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the method according to any one of claims 1 to 8.

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