Method and apparatus for coordinating a bidirectional link, electronic device, and storage medium

Abstract

The application provides a coordination method and device of a bidirectional link, electronic equipment and a storage medium, wherein the coordination method of the bidirectional link comprises: monitoring link state information of an uplink and a downlink in real time; determining a delay category of each data flow in the uplink and the downlink; dynamically calculating a priority weight of each data flow based on the link state information of the uplink and the downlink; adjusting a transmission strategy of the uplink and the downlink based on the priority weight of each data flow; and adjusting the transmission strategy of the uplink and the downlink based on the delay category of each data flow. The application can at least improve the dynamic adaptability of a link, so as to better meet the QoS and RTT delay requirements of various applications under different network conditions.

Description

Technical Field

[0001] This application relates to the field of 5G mobile communications, and more specifically, to a method, apparatus, electronic device, and storage medium for coordinating a two-way link. Background Technology

[0002] Currently, existing bidirectional link coordination methods cannot adapt to real-time changes in network conditions, and therefore cannot flexibly meet the QoS and RTT latency requirements of various applications. Summary of the Invention

[0003] The purpose of this application is to provide a method, apparatus, electronic device, and storage medium for coordinating bidirectional links, so as to improve the dynamic adaptability of the links and better meet the QoS and RTT latency requirements of various applications under different network conditions.

[0004] The first aspect of this application discloses a coordination method for a bidirectional link, the method comprising:

[0005] Real-time monitoring of uplink and downlink link status information;

[0006] Determine the latency category of each data stream in the uplink and downlink;

[0007] The priority weight of each data stream is dynamically calculated based on the link status information of the uplink and downlink;

[0008] The transmission strategy of the uplink and downlink is adjusted based on the priority weight of each data stream;

[0009] The uplink and downlink transmission strategies are adjusted based on the latency category of each data stream.

[0010] The first aspect of this application is that it can monitor the link status information of the uplink and downlink in real time and determine the delay category of each data stream in the uplink and downlink. Then, it can dynamically calculate the priority weight of each data stream based on the link status information of the uplink and downlink, adjust the transmission strategy of the uplink and downlink based on the priority weight of each data stream, and adjust the transmission strategy of the uplink and downlink based on the delay category of each data stream. In this way, the transmission strategy of the uplink and downlink can be adjusted in real time based on the changes in the link status of the uplink and downlink, thereby better meeting the QoS and RTT delay requirements of various applications under different network conditions.

[0011] On the other hand, through actual time consumption tests, the execution of the method in the first aspect of this application requires fewer computational resources. Furthermore, by dynamically adjusting priority weights, this application can achieve a reasonable allocation of resources between high-priority and low-priority applications, thereby avoiding resource waste and improving overall network performance.

[0012] In a first aspect of this application, as an optional implementation, determining the latency category of each data stream in the uplink and downlink includes:

[0013] Obtain the application type, latency requirements, and business scenario information for each data stream;

[0014] The latency category of each data stream is determined based on at least one of the following: application type of each data stream, latency requirement information of each data stream, and business scenario information.

[0015] This optional implementation can obtain the application type, latency requirement information and business scenario information of each data stream, and then determine the latency category of each data stream based on at least one of the application type, latency requirement information and business scenario information of each data stream.

[0016] In the first aspect of this application, as an optional implementation, the link status information of the uplink and downlink includes real-time transmission parameters for each data stream;

[0017] And, the dynamic calculation of the priority weight of each data stream based on the link state information of the uplink and downlink includes:

[0018] The real-time transmission parameters of each data stream are used as fuzzy variables and a membership function based on the fuzzy variables to calculate the membership value of each data stream.

[0019] The fuzzy inference result is determined based on the fuzzy rule base and the membership value of each data stream;

[0020] The fuzzy inference results are processed using the centroid method or the area method to obtain the priority weight of each data stream.

[0021] This optional implementation can use the real-time transmission parameters of each data stream as fuzzy variables and a membership function based on the fuzzy variables to calculate the membership value of each data stream. Then, it can determine the fuzzy inference result based on the fuzzy rule base and the membership value of each data stream. Finally, it can process the fuzzy inference result based on the centroid method or the area method to obtain the priority weight of each data stream.

[0022] In a first aspect of this application, as an optional implementation, adjusting the uplink and downlink transmission strategy based on the priority weight of each data stream includes:

[0023] Based on the priority weight of each data stream, each data stream is sorted in descending order of weight value to generate a sorting result;

[0024] The uplink and downlink transmission strategies are adjusted based on the sorting results.

[0025] This optional implementation can sort each data stream according to its priority weight in descending order of weight value to generate a sorting result, and then adjust the uplink and downlink transmission strategy based on the sorting result.

[0026] In a first aspect of this application, as an optional implementation, adjusting the uplink and downlink transmission strategy based on the delay category of each data stream includes:

[0027] When the latency category of the data stream is a low-latency data stream, the transmission strategy of the uplink and downlink is adjusted based on the bandwidth reservation mechanism so that the data stream has reserved bandwidth;

[0028] When the latency category of the data stream is a high-latency data stream, the priority of the data stream is reduced;

[0029] When the data stream has a latency category of medium latency requirement, the bandwidth allocation of the uplink and downlink is adjusted based on the real-time transmission parameters of the data stream.

[0030] This optional implementation can adjust the uplink and downlink transmission strategies based on a bandwidth reservation mechanism when the data stream has a low latency requirement, so that the data stream has reserved bandwidth; when the data stream has a high latency requirement, the priority of the data stream is reduced; and when the data stream has a medium latency requirement, the bandwidth allocation of the uplink and downlink is adjusted based on the real-time transmission parameters of the data stream.

[0031] In a first aspect of this application, as an optional implementation, after adjusting the uplink and downlink transmission strategies based on the delay category of each data stream, the method further includes:

[0032] The real-time transmission parameters of the data stream are periodically collected, and the deviation between the real-time transmission parameters of the data stream and the reference value is calculated.

[0033] The deviation between the real-time transmission parameters of the data stream and the reference value is used as feedback data, and the transmission strategies of the uplink and downlink are adjusted based on the feedback data.

[0034] This optional implementation can periodically collect the real-time transmission parameters of the data stream and calculate the deviation between the real-time transmission parameters of the data stream and the reference value. Then, the deviation between the real-time transmission parameters of the data stream and the reference value can be used as feedback data, and the transmission strategy of the uplink and downlink can be adjusted based on the feedback data. In this way, a feedback mechanism can be formed, and the real-time performance and fairness can be balanced based on the feedback mechanism.

[0035] In a first aspect of this application, as an optional implementation, after adjusting the uplink and downlink transmission strategies based on the feedback data, the method further includes:

[0036] The feedback data is processed based on a preset transmission model and control algorithm to obtain a prediction result of the transmission quality change trend.

[0037] The uplink and downlink transmission strategies are adjusted based on the predicted trend of transmission quality changes.

[0038] This optional implementation can process the feedback data based on a preset transmission model and control algorithm to obtain a prediction result of the transmission quality change trend, and then adjust the transmission strategy of the uplink and downlink based on the prediction result of the transmission quality change trend.

[0039] A second aspect of this application discloses a coordination device for a bidirectional link, the device comprising:

[0040] The monitoring module is used to monitor the link status information of uplink and downlink in real time;

[0041] A determination module is used to determine the delay category of each data stream in the uplink and downlink;

[0042] The dynamic calculation module is used to dynamically calculate the priority weight of each data stream based on the link status information of the uplink and downlink;

[0043] The first adjustment module is used to adjust the transmission strategy of the uplink and downlink based on the priority weight of each data stream;

[0044] The second adjustment module is used to adjust the transmission strategy of the uplink and downlink based on the delay category of each data stream.

[0045] The apparatus of the second aspect of this application can monitor the link status information of the uplink and downlink in real time and determine the delay category of each data stream in the uplink and downlink. It can then dynamically calculate the priority weight of each data stream based on the link status information of the uplink and downlink, adjust the transmission strategy of the uplink and downlink based on the priority weight of each data stream, and adjust the transmission strategy of the uplink and downlink based on the delay category of each data stream. In this way, the transmission strategy of the uplink and downlink can be adjusted in real time based on the changes in the link status of the uplink and downlink, thereby better meeting the QoS and RTT delay requirements of various applications under different network conditions.

[0046] On the other hand, actual time consumption tests show that this application requires fewer computational resources. Furthermore, by dynamically adjusting priority weights, this application can achieve a reasonable allocation of resources between high-priority and low-priority applications, thereby avoiding resource waste and improving overall network performance.

[0047] A third aspect of this application discloses an electronic device, wherein the electronic device includes:

[0048] Processor; and

[0049] The memory is configured to store machine-readable instructions that, when executed by the processor, perform the bidirectional link coordination method of the first aspect of this application.

[0050] The electronic device of the third aspect of this application can monitor the link status information of the uplink and downlink in real time and determine the delay category of each data stream in the uplink and downlink. It can then dynamically calculate the priority weight of each data stream based on the link status information of the uplink and downlink, adjust the transmission strategy of the uplink and downlink based on the priority weight of each data stream, and adjust the transmission strategy of the uplink and downlink based on the delay category of each data stream. In this way, the transmission strategy of the uplink and downlink can be adjusted in real time based on the changes in the link status of the uplink and downlink, thereby better meeting the QoS and RTT delay requirements of various applications under different network conditions.

[0051] On the other hand, actual time consumption tests show that this application requires fewer computational resources. Furthermore, by dynamically adjusting priority weights, this application can achieve a reasonable allocation of resources between high-priority and low-priority applications, thereby avoiding resource waste and improving overall network performance.

[0052] The fourth aspect of this application discloses a storage medium storing a computer program, which is executed by a processor using the bidirectional link coordination method described in the first aspect of this application.

[0053] The storage medium of the fourth aspect of this application can monitor the link status information of the uplink and downlink in real time and determine the latency category of each data stream in the uplink and downlink. It can then dynamically calculate the priority weight of each data stream based on the link status information of the uplink and downlink, adjust the transmission strategy of the uplink and downlink based on the priority weight of each data stream, and adjust the transmission strategy of the uplink and downlink based on the latency category of each data stream. In this way, the transmission strategy of the uplink and downlink can be adjusted in real time based on the changes in the link status of the uplink and downlink, thereby better meeting the QoS and RTT latency requirements of various applications under different network conditions.

[0054] On the other hand, actual time consumption tests show that this application requires fewer computational resources. Furthermore, by dynamically adjusting priority weights, this application can achieve a reasonable allocation of resources between high-priority and low-priority applications, thereby avoiding resource waste and improving overall network performance. Attached Figure Description

[0055] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0056] Figure 1 This is a flowchart illustrating a bidirectional link coordination method disclosed in an embodiment of this application;

[0057] Figure 2 This is a schematic diagram of the structure of a bidirectional link coordination device disclosed in an embodiment of this application;

[0058] Figure 3 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application. Detailed Implementation

[0059] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0060] Example 1

[0061] Please see Figure 1 , Figure 1 This is a flowchart illustrating a bidirectional link coordination method disclosed in an embodiment of this application, as shown below. Figure 1 As shown, the method in this application embodiment includes the following steps:

[0062] 101. Monitor the link status information of uplink and downlink in real time;

[0063] 102. Determine the latency category of each data stream in the uplink and downlink;

[0064] 103. Dynamically calculate the priority weight of each data stream based on the link status information of uplink and downlink;

[0065] 104. Adjust the uplink and downlink transmission strategies based on the priority weight of each data stream;

[0066] 105. Adjust the uplink and downlink transmission strategies based on the latency category of each data stream.

[0067] The embodiments of this application can monitor the link status information of uplink and downlink in real time and determine the delay category of each data stream in uplink and downlink. Then, it can dynamically calculate the priority weight of each data stream based on the link status information of uplink and downlink, adjust the transmission strategy of uplink and downlink based on the priority weight of each data stream, and adjust the transmission strategy of uplink and downlink based on the delay category of each data stream. In this way, the transmission strategy of uplink and downlink can be adjusted in real time based on the changes in the link status of uplink and downlink, thereby better meeting the QoS and RTT delay requirements of various applications under different network conditions.

[0068] On the other hand, through actual time consumption tests, the execution of the method in the first aspect of this application requires fewer computational resources. Furthermore, by dynamically adjusting priority weights, this application can achieve a reasonable allocation of resources between high-priority and low-priority applications, thereby avoiding resource waste and improving overall network performance.

[0069] In this embodiment, for step 101, the link state information of the uplink and downlink includes the real-time transmission parameters of each data stream. For example, the link state information of the uplink and downlink includes the real-time transmission parameters of six data streams. Further, the real-time transmission parameters of the data streams include parameters such as RTT delay, packet loss rate, link quality, and congestion level. Further, network probes, sniffers, and other tools can be used to monitor the transmission status of data streams in the network, thereby obtaining the real-time transmission parameters of the data streams. For example, for each data stream, its current RTT delay on the UPF network element can be measured by sending probe packets or analyzing data packets during transmission. That is, on the UPF network element, probe packets are periodically sent to the target node. After receiving the probe packets, the target node immediately returns an acknowledgment packet. The UPF network element calculates the time difference between sending the probe packet and receiving the acknowledgment packet, which is the RTT delay. The RTT delay is obtained by averaging the continuously measured RTT delays using the sliding window averaging method. Averaging the continuously measured RTT delays using the sliding window averaging method can reduce the impact of instantaneous fluctuations on the results. In this embodiment of the application, link quality can be evaluated by measuring parameters such as signal-to-noise ratio (SNR) or bit error rate (BER).

[0070] In this embodiment of the application, as an optional implementation, step 102: determining the latency category of each data stream in the uplink and downlink includes the following sub-steps:

[0071] Obtain the application type, latency requirements, and business scenario information for each data stream;

[0072] The latency category of each data stream is determined based on at least one of the following: application type, latency requirement information, and business scenario information.

[0073] This optional implementation can obtain the application type, latency requirement information, and business scenario information of each data stream, and then determine the latency category of each data stream based on at least one of the application type, latency requirement information, and business scenario information of each data stream.

[0074] In this embodiment of the application, as an optional implementation, the step of dynamically calculating the priority weight of each data stream based on the link state information of the uplink and downlink includes the following sub-steps:

[0075] The real-time transmission parameters of each data stream are used as fuzzy variables and a membership function based on the fuzzy variables to calculate the membership value of each data stream.

[0076] The fuzzy inference result is determined based on the fuzzy rule base and the membership value of each data stream;

[0077] The fuzzy inference results are processed using the centroid method or area method to obtain the priority weight of each data stream.

[0078] This optional implementation can use the real-time transmission parameters of each data stream as fuzzy variables and a membership function based on the fuzzy variables to calculate the membership value of each data stream. Then, it can determine the fuzzy inference result based on the fuzzy rule base and the membership value of each data stream. Finally, it can process the fuzzy inference result based on the centroid method or the area method to obtain the priority weight of each data stream.

[0079] Regarding the above optional implementation methods, the membership function of the fuzzy variable can take the fuzzy variable as an input value and map the input value to a range of membership values. Further, the membership function of the fuzzy variable can be one of a triangular membership function, a Gaussian membership function, or a trapezoidal membership function. Further, for the fuzzy variable of RTT delay, a triangular membership function can be selected; specifically, the triangular membership function is as follows:

[0080] Nearest range: 0ms to 50ms, membership degree is 1-x / 50;

[0081] Medium: 30ms~100ms, membership degree value is (x-30) / 70;

[0082] Distance: 80ms~200ms, membership degree value is (200-x) / 120.

[0083] Furthermore, for the fuzzy variable of packet loss rate, a trapezoidal membership function can be chosen, where the trapezoidal membership function is:

[0084] Low: 0% to 1%, membership degree value is 1-x / 1;

[0085] Medium: 0.5%~5%, membership degree value is (x-0.5) / 4.5;

[0086] High: 3% to 10%, membership degree value is (10-x) / 7.

[0087] For the above optional implementation methods, the fuzzy rule base is specifically as follows:

[0088] IF RTT delay is close AND packet loss rate is low THEN weight is high;

[0089] IF RTT delay is in AND packet loss rate is in THEN weight is in;

[0090] If the RTT delay is high and the packet loss rate is high, then the weight is low.

[0091] Regarding the above optional implementation methods, a specific way to process the fuzzy inference results based on the centroid method or area method to obtain the priority weight of each data stream is as follows:

[0092] Use the fuzzy inference result as the output variable and determine the membership function of the output variable;

[0093] Calculate the membership value of the output variable based on the membership function of the output variable;

[0094] The centroid position is determined based on the membership values ​​of the output variables;

[0095] The priority weight of a data stream is determined based on its centroid position. As an example, suppose the fuzzy inference result is "medium" and its membership value is 1. Then its centroid position is 0.5. Therefore, the priority weight of the data stream is 0.5. That is, when the priority weight is "medium", the corresponding weight value is 0.5.

[0096] For the above optional implementation method, the membership function of the output variable can be a triangular membership function, wherein the triangular membership function is:

[0097] Low: 0~0.33, membership value is 1-x / 0.33;

[0098] Medium: 0.17~0.83, membership degree value is (x-0.17) / 0.66;

[0099] High: 0.67~1, membership degree value is (x-0.67) / 0.33.

[0100] In this application embodiment, as an optional implementation, adjusting the uplink and downlink transmission strategy based on the priority weight of each data stream includes:

[0101] Based on the priority weight of each data stream, each data stream is sorted in descending order of weight value to generate a sorting result;

[0102] Adjust the uplink and downlink transmission strategies based on the sorting results.

[0103] This optional implementation can sort each data stream according to its priority weight, in descending order of weight value, to generate a sorting result, and then adjust the uplink and downlink transmission strategies based on the sorting result.

[0104] For the above optional implementation method, assuming the input data is a list of tuples containing data stream names and priority weights, such as: [("data_stream_1",0.8),("data_stream_2",0.6),("data_stream_3",0.9),("data_stream_4",0.4)], then sorted according to priority weight from high to low, the sorted result is: data_stream_3 0.9, data_stream_1 0.8, data_stream_2 0.6, data_stream_4 0.4.

[0105] For the above optional implementation methods, the specific way to adjust the uplink and downlink transmission strategies based on the sorting results is as follows:

[0106] First, allocate more bandwidth resources to data streams with higher weighting to ensure their transmission quality.

[0107] Second, when network congestion occurs, prioritize processing data streams with higher weights to reduce their transmission delay.

[0108] Third, for data streams with lower weights, they can be transmitted when the network is idle to make full use of network resources.

[0109] In this embodiment of the application, as an optional implementation, the step of adjusting the uplink and downlink transmission strategies based on the delay category of each data stream includes the following sub-steps:

[0110] When the data stream has a low latency requirement, the uplink and downlink transmission strategies are adjusted based on the bandwidth reservation mechanism to ensure that the data stream has reserved bandwidth. At the same time, for low latency data streams, the shortest path algorithm and congestion control algorithm are used to ensure the timeliness and transmission quality of the data stream.

[0111] When the data stream has a high latency requirement, the priority of the data stream is reduced. Among them, the longest queuing time first scheduling algorithm can be used to place the high latency data stream at the end of the queue (sorting result) to ensure the timely transmission of the low latency data stream.

[0112] When the data stream has a latency category of medium latency requirement, the uplink and downlink bandwidth allocation is adjusted based on the real-time transmission parameters of the data stream.

[0113] This optional implementation can adjust the uplink and downlink transmission strategies based on a bandwidth reservation mechanism when the data stream has a low latency requirement, so that the data stream has reserved bandwidth; when the data stream has a high latency requirement, the priority of the data stream is reduced; and when the data stream has a medium latency requirement, the bandwidth allocation of the uplink and downlink is adjusted based on the real-time transmission parameters of the data stream.

[0114] In this embodiment of the application, as an optional implementation, after step 1: adjusting the uplink and downlink transmission strategies based on the delay category of each data stream, the method of this embodiment further includes the following steps:

[0115] Periodically collect the real-time transmission parameters of the data stream and calculate the deviation between the real-time transmission parameters of the data stream and the reference value;

[0116] The deviation between the real-time transmission parameters of the data stream and the reference value is used as feedback data, and the transmission strategies of the uplink and downlink are adjusted based on the feedback data.

[0117] This optional implementation can periodically collect real-time transmission parameters of the data stream and calculate the deviation between the real-time transmission parameters of the data stream and the reference value. Then, the deviation between the real-time transmission parameters of the data stream and the reference value can be used as feedback data, and the transmission strategies of the uplink and downlink can be adjusted based on the feedback data. In this way, a feedback mechanism can be formed, and the real-time performance and fairness can be balanced based on the feedback mechanism.

[0118] Regarding the above optional implementation methods, a further specific way to calculate the deviation between the real-time transmission parameters of the data stream and the reference value is as follows:

[0119] Calculate comprehensive evaluation indicators based on real-time transmission parameters of data streams;

[0120] Calculate the deviation between the comprehensive evaluation index and the reference value.

[0121] Furthermore, based on the real-time transmission parameters of the data stream, the formula for calculating the comprehensive evaluation index is as follows:

[0122] NTQI = α * RTT latency + β * packet loss rate + γ * link quality

[0123] Wherein, NTQI represents a comprehensive evaluation index, and α, β, and γ are weighting coefficients.

[0124] Regarding the above optional implementation method, another specific way to calculate the deviation between the real-time transmission parameters of the data stream and the reference value is as follows:

[0125] Based on the deviation between each real-time transmission parameter and its corresponding reference value, for example, for the real-time transmission parameter RTT delay, its corresponding reference value can be 10ms, the deviation between the real-time RTT delay and 10ms is calculated.

[0126] Furthermore, a specific method for adjusting the uplink and downlink transmission strategies based on feedback data is as follows:

[0127] If the deviation is positive, the bandwidth allocation for the data stream can be increased to speed up transmission and reduce latency; if the deviation is negative, the bandwidth allocation for the data stream can be reduced to reduce network congestion and improve transmission quality.

[0128] For the above optional implementation methods, a deviation range can be set. If the deviation between the real-time transmission parameter and its corresponding reference value falls within the deviation range, the transmission strategy is not adjusted. If it exceeds the deviation range, the transmission strategy is adjusted. For example, for the real-time transmission parameter RTT delay, the corresponding deviation range is ±2ms. If the deviation of the real-time transmission parameter RTT delay from 10ms is within the range of ±2ms, no adjustment is made.

[0129] In this embodiment of the application, as an optional implementation, after step 1: adjusting the uplink and downlink transmission strategies based on feedback data, the method of this embodiment further includes the following steps:

[0130] Based on the preset transmission model and control algorithm, the feedback data is processed to obtain the prediction results of the transmission quality change trend.

[0131] Adjust uplink and downlink transmission strategies based on the predicted trends in transmission quality.

[0132] This optional implementation can process feedback data based on a preset transmission model and control algorithm to obtain a prediction result of the transmission quality change trend. Then, it can adjust the transmission strategy of uplink and downlink based on the prediction result of the transmission quality change trend. Since the feedback mechanism formed by the deviation cannot accurately adjust the transmission strategy in some scenarios, this optional implementation can evaluate the effect of the feedback data on the adjustment of the transmission strategy based on the prediction result of the transmission quality change trend, and then adjust the transmission strategy more accurately based on the evaluation result.

[0133] Example 2

[0134] Please see Figure 2 , Figure 2 This is a schematic diagram of the structure of a bidirectional link coordination device disclosed in an embodiment of this application, as shown below. Figure 2 As shown, the apparatus in this application embodiment includes the following functional modules:

[0135] Monitoring module 201 is used to monitor the link status information of uplink and downlink in real time;

[0136] The determination module 202 is used to determine the delay category of each data stream in the uplink and downlink;

[0137] The dynamic calculation module 203 is used to dynamically calculate the priority weight of each data stream based on the link status information of the uplink and downlink.

[0138] The first adjustment module 204 is used to adjust the transmission strategy of the uplink and downlink based on the priority weight of each data stream;

[0139] The second adjustment module 205 is used to adjust the transmission strategy of the uplink and downlink based on the delay category of each data stream.

[0140] The apparatus of this application embodiment can monitor the link status information of uplink and downlink in real time and determine the delay category of each data stream in uplink and downlink. It can then dynamically calculate the priority weight of each data stream based on the link status information of uplink and downlink, adjust the transmission strategy of uplink and downlink based on the priority weight of each data stream, and adjust the transmission strategy of uplink and downlink based on the delay category of each data stream. In this way, the transmission strategy of uplink and downlink can be adjusted in real time based on the changes in the link status of uplink and downlink, thereby better meeting the QoS and RTT delay requirements of various applications under different network conditions.

[0141] On the other hand, actual time consumption tests show that this application requires fewer computational resources. Furthermore, by dynamically adjusting priority weights, this application can achieve a reasonable allocation of resources between high-priority and low-priority applications, thereby avoiding resource waste and improving overall network performance.

[0142] It should be noted that for other detailed descriptions of the apparatus in the embodiments of this application, please refer to the relevant description in Embodiment 1 of this application, which will not be repeated in the embodiments of this application.

[0143] Example 3

[0144] Please see Figure 3 , Figure 3 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application, such as... Figure 3 As shown, the electronic device in this application embodiment includes:

[0145] Processor 301; and

[0146] The memory 302 is configured to store machine-readable instructions that, when executed by the processor 301, perform the bidirectional link coordination method of this application embodiment.

[0147] The electronic device in this application embodiment can monitor the link status information of the uplink and downlink in real time and determine the delay category of each data stream in the uplink and downlink. Then, it can dynamically calculate the priority weight of each data stream based on the link status information of the uplink and downlink, adjust the transmission strategy of the uplink and downlink based on the priority weight of each data stream, and adjust the transmission strategy of the uplink and downlink based on the delay category of each data stream. In this way, the transmission strategy of the uplink and downlink can be adjusted in real time based on the changes in the link status of the uplink and downlink, thereby better meeting the QoS and RTT delay requirements of various applications under different network conditions.

[0148] On the other hand, actual time consumption tests show that this application requires fewer computational resources. Furthermore, by dynamically adjusting priority weights, this application can achieve a reasonable allocation of resources between high-priority and low-priority applications, thereby avoiding resource waste and improving overall network performance.

[0149] Example 4

[0150] This application discloses a storage medium storing a computer program, which is executed by a processor using the bidirectional link coordination method of this application.

[0151] The storage medium in this application embodiment can monitor the link status information of the uplink and downlink in real time and determine the latency category of each data stream in the uplink and downlink. It can then dynamically calculate the priority weight of each data stream based on the link status information of the uplink and downlink, adjust the transmission strategy of the uplink and downlink based on the priority weight of each data stream, and adjust the transmission strategy of the uplink and downlink based on the latency category of each data stream. In this way, the transmission strategy of the uplink and downlink can be adjusted in real time based on the changes in the link status of the uplink and downlink, thereby better meeting the QoS and RTT latency requirements of various applications under different network conditions.

[0152] On the other hand, actual time consumption tests show that this application requires fewer computational resources. Furthermore, by dynamically adjusting priority weights, this application can achieve a reasonable allocation of resources between high-priority and low-priority applications, thereby avoiding resource waste and improving overall network performance.

[0153] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and there may be other division methods in actual implementation. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interface; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0154] Furthermore, the units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0155] Furthermore, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0156] It should be noted that if a function is implemented as a software module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0157] In this document, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, without necessarily requiring or implying any such actual relationship or order between these entities or operations.

[0158] The above are merely embodiments of this application and are not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A coordination method for a bidirectional link, characterized in that, The method includes: Real-time monitoring of uplink and downlink link status information; Determine the latency category of each data stream in the uplink and downlink; The priority weight of each data stream is dynamically calculated based on the link status information of the uplink and downlink; The transmission strategy of the uplink and downlink is adjusted based on the priority weight of each data stream; The uplink and downlink transmission strategies are adjusted based on the latency category of each data stream; Furthermore, the link status information of the uplink and downlink includes the real-time transmission parameters of each data stream; And, the dynamic calculation of the priority weight of each data stream based on the link state information of the uplink and downlink includes: The real-time transmission parameters of each data stream are used as fuzzy variables and a membership function based on the fuzzy variables to calculate the membership value of each data stream. The fuzzy inference result is determined based on the fuzzy rule base and the membership value of each data stream; The fuzzy inference results are processed using the centroid method or the area method to obtain the priority weight of each data stream.

2. The method as described in claim 1, characterized in that, Determining the latency category of each data stream in the uplink and downlink includes: Obtain the application type, latency requirements, and business scenario information for each data stream; The latency category of each data stream is determined based on at least one of the following: application type of each data stream, latency requirement information of each data stream, and business scenario information.

3. The method as described in claim 2, characterized in that, The adjustment of the uplink and downlink transmission strategy based on the priority weight of each data stream includes: Based on the priority weight of each data stream, each data stream is sorted in descending order of weight value to generate a sorting result; The uplink and downlink transmission strategies are adjusted based on the sorting results.

4. The method as described in claim 3, characterized in that, The adjustment of the uplink and downlink transmission strategy based on the delay category of each data stream includes: When the latency category of the data stream is a low-latency data stream, the transmission strategy of the uplink and downlink is adjusted based on the bandwidth reservation mechanism so that the data stream has reserved bandwidth; When the latency category of the data stream is a high-latency data stream, the priority of the data stream is reduced; When the data stream has a latency category of medium latency requirement, the bandwidth allocation of the uplink and downlink is adjusted based on the real-time transmission parameters of the data stream.

5. The method as described in claim 1, characterized in that, After adjusting the uplink and downlink transmission strategies based on the delay category of each data stream, the method further includes: The real-time transmission parameters of the data stream are periodically collected, and the deviation between the real-time transmission parameters of the data stream and the reference value is calculated. The deviation between the real-time transmission parameters of the data stream and the reference value is used as feedback data, and the transmission strategies of the uplink and downlink are adjusted based on the feedback data.

6. The method as described in claim 5, characterized in that, After adjusting the uplink and downlink transmission strategies based on the feedback data, the method further includes: The feedback data is processed based on a preset transmission model and control algorithm to obtain a prediction result of the transmission quality change trend. The uplink and downlink transmission strategies are adjusted based on the predicted trend of transmission quality changes.

7. A coordination device for a bidirectional link, characterized in that, The device includes: The monitoring module is used to monitor the link status information of uplink and downlink in real time; A determination module is used to determine the delay category of each data stream in the uplink and downlink; The dynamic calculation module is used to dynamically calculate the priority weight of each data stream based on the link status information of the uplink and downlink; The first adjustment module is used to adjust the transmission strategy of the uplink and downlink based on the priority weight of each data stream; The second adjustment module is used to adjust the transmission strategy of the uplink and downlink based on the delay category of each data stream; Furthermore, the link status information of the uplink and downlink includes the real-time transmission parameters of each data stream; And, the dynamic calculation of the priority weight of each data stream based on the link state information of the uplink and downlink includes: The real-time transmission parameters of each data stream are used as fuzzy variables and a membership function based on the fuzzy variables to calculate the membership value of each data stream. The fuzzy inference result is determined based on the fuzzy rule base and the membership value of each data stream; The fuzzy inference results are processed based on the centroid method or the area method to obtain the priority weight of each data stream.

8. An electronic device, characterized in that, include: processor; as well as The memory is configured to store machine-readable instructions that, when executed by the processor, perform the bidirectional link coordination method as described in any one of claims 1-6.

9. A storage medium, characterized in that, The storage medium stores a computer program, which is executed by a processor as the coordination method for a bidirectional link as described in any one of claims 1-6.

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