Network state monitoring and optimization processing method and device and readable storage medium

Abstract

The invention provides a network state monitoring and optimization processing method and device and a readable storage medium. The method comprises the steps of obtaining network state parameters through monitoring; determining data transmission parameters according to the network state parameters; determining the transmission priority of the target data according to the importance requirement and the real-time requirement of the target data to be transmitted; and based on the data transmission parameter and the transmission priority, a target path is adopted to carry out data transmission on the target data, and the target path is a preset main path or a standby path with the highest stability when the preset main path is unavailable. According to the method, the parameters can be adjusted in real time according to the network condition, the data transmission process can be optimized according to different service requirements, the capability of flexibly coping with unexpected conditions is achieved, and the data communication quality and the user experience are remarkably improved.

Description

Technical Field

[0001] The present application relates to the field of Internet technology, and in particular to a network status monitoring and optimization processing method, device and readable storage medium. Background Art

[0002] Under unstable network conditions, the loss of data packets may cause the interruption of inspection tasks. This situation will not only affect the inspection efficiency, but also cause the omission of important information, which will lead to the failure to timely discover and deal with equipment operation hazards.

[0003] In addition, the interruption of inspection tasks may also cause a series of chain reactions, such as chaos in production scheduling, increased safety hazards, and increased maintenance costs, which will have an adverse impact on the normal operation of the enterprise.

[0004] Therefore, in an unstable network environment, how to take effective measures to reduce the packet loss rate and ensure the smooth progress of inspection tasks is of great significance to ensuring production safety and improving enterprise benefits. Summary of the invention

[0005] The technical problem to be solved by the present application is to provide a network status monitoring and optimization processing method, device and readable storage medium to solve the problems existing in the prior art in view of the above-mentioned deficiencies in the prior art.

[0006] In a first aspect, the present application provides a network status monitoring and optimization processing method, the method comprising:

[0007] S1. Obtain network status parameters through monitoring;

[0008] S2. Determine data transmission parameters according to the network status parameters;

[0009] S3. Determine the transmission priority of the target data according to the importance and real-time requirements of the target data to be transmitted;

[0010] S4. Based on the data transmission parameters and the transmission priority, adopt a target path to perform data transmission on the target data, wherein the target path is a preset main path or a backup path with the highest stability when the preset main path is unavailable.

[0011] In some embodiments, the network status parameters include network bandwidth and data packet transmission delay, and the data transmission parameters include transmission rate;

[0012] S2, including:

[0013] The transmission rate is determined based on the network bandwidth and data packet transmission delay.

[0014] In some embodiments, the transmission rate is determined by the following formula based on the network bandwidth and the data packet transmission delay:

[0015] R=W / (1+D)

[0016] Among them, W represents the network bandwidth, D represents the data packet transmission delay, and R represents the transmission rate.

[0017] In some embodiments, the network status parameters include packet loss rate and network delay, and the data transmission parameters include retransmission interval, number of retransmissions and data fragment size;

[0018] S2, including:

[0019] The retransmission interval and number of retransmissions of the data transmission protocol are determined according to the packet loss rate and network delay, and the data segment size is dynamically adjusted.

[0020] In some embodiments, determining the retransmission interval and the number of retransmissions of the data transmission protocol according to the packet loss rate and the network delay includes:

[0021] Determine the adjustment factor based on the packet loss rate and network delay;

[0022] When the adjustment factor is greater than the first preset threshold, the retransmission interval is increased, and when the adjustment factor is less than or equal to the first preset threshold, the retransmission interval is kept unchanged;

[0023] When the adjustment factor is greater than the second preset threshold, the number of retransmissions is increased, and when the adjustment factor is less than or equal to the second preset threshold, the number of retransmissions is kept unchanged;

[0024] The second preset threshold is greater than the first preset threshold.

[0025] In some embodiments, based on the packet loss rate and the network delay, the adjustment factor is determined by the following formula:

[0026] K=P×T / C

[0027] Among them, P represents the packet loss rate, T represents the network delay, K represents the adjustment factor, and C is a constant representing the reference value.

[0028] In some embodiments, the data shard size is dynamically adjusted by the following formula:

[0029] data_packet_size

[0030] =max(default_packet_size-delay_factor

[0031] ×delay,min_packet_size)

[0032] Among them, data_packet_size indicates the data fragment size, default_packet_size indicates the default data packet size, delay is the network delay, min_pcaket_size is the minimum data packet size, and delay_factor is the delay adjustment factor.

[0033] In some embodiments, in S3, according to the importance and real-time requirements of the target data to be transmitted, the transmission priority of the target data is determined by the following formula:

[0034] P=(Q+V) / 2

[0035] Among them, P represents the transmission priority, Q represents the importance requirement of the target data, and V represents the real-time requirement of the target data.

[0036] In some embodiments, in S4, the backup path with the highest stability when the preset main path is unavailable is determined by the following formula:

[0037] S = min(Pi,Ci),

[0038] Wherein, S represents the backup path with the highest stability when the preset main path is unavailable, Pi represents the priority of the i-th transmission path, and Ci represents the stability of the i-th transmission path.

[0039] In a second aspect, the present application provides a network status monitoring and optimization processing device, the device comprising:

[0040] A parameter acquisition module, which is configured to acquire network status parameters through monitoring;

[0041] a parameter determination module, configured to determine a data transmission parameter according to the network status parameter;

[0042] A priority determination module, configured to determine the transmission priority of the target data to be transmitted according to the importance requirement and real-time requirement of the target data to be transmitted;

[0043] A data transmission module is configured to transmit the target data using a target path based on the data transmission parameters and the transmission priority, wherein the target path is a preset main path or a backup path with the highest stability when the preset main path is unavailable.

[0044] In a third aspect, the present application provides a network status monitoring and optimization processing device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to implement the network status monitoring and optimization processing method described in the first aspect above.

[0045] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the network status monitoring and optimization processing method described in the first aspect is implemented.

[0046] The network status monitoring and optimization processing method, device and readable storage medium provided by the present application include: obtaining network status parameters through monitoring; determining data transmission parameters according to the network status parameters; determining the transmission priority of the target data to be transmitted according to the importance and real-time requirements of the target data to be transmitted; based on the data transmission parameters and the transmission priority, using the target path to transmit the target data, wherein the target path is a preset main path or a backup path with the highest stability when the preset main path is unavailable. The method of the present application can not only adjust parameters in real time according to network conditions, but also optimize the data transmission process according to different business needs, and has the ability to flexibly respond to unexpected situations, significantly improving the quality of data communication and user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0048] Figure 1 A flowchart of a network status monitoring and optimization processing method provided in an embodiment of the present application;

[0049] Figure 2 A schematic diagram of a network status monitoring and optimization processing method provided in an embodiment of the present application;

[0050] Figure 3 A schematic diagram of the structure of a network status monitoring and optimization processing device provided in an embodiment of the present application;

[0051] Figure 4 A schematic diagram of the structure of another network status monitoring and optimization processing device provided in an embodiment of the present application.

[0052] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0053] In order to enable those skilled in the art to better understand the technical solution of the present application, the implementation mode of the present application will be further described in detail below with reference to the accompanying drawings.

[0054] It should be understood that the specific embodiments and drawings described herein are only used to explain the present application, rather than to limit the present application.

[0055] It can be understood that, in the absence of conflict, the various embodiments in the present application and the various features in the embodiments can be combined with each other.

[0056] It can be understood that, for the convenience of description, the drawings of the present application only show the parts related to the present application, while the parts unrelated to the present application are not shown in the drawings.

[0057] It can be understood that each unit and module involved in the embodiments of the present application may correspond to only one physical structure, or may be composed of multiple physical structures, or multiple units and modules may be integrated into one physical structure.

[0058] It can be understood that the terms "first", "second", etc. in the embodiments of the present application are used to distinguish different objects, or to distinguish different processing of the same object, rather than to describe a specific order of objects.

[0059] It is understandable that, in the absence of conflict, the functions and steps marked in the flowcharts and block diagrams of the present application may occur in an order different from that marked in the drawings.

[0060] It is understood that the flowcharts and block diagrams of the present application illustrate the possible architectures, functions, and operations of the systems, devices, equipment, and methods according to the various embodiments of the present application. Among them, each box in the flowchart or block diagram may represent a unit, module, program segment, code, which contains executable instructions for implementing the specified functions. Moreover, each box or combination of boxes in the block diagram and flowchart may be implemented by a hardware-based system that implements the specified functions, or by a combination of hardware and computer instructions.

[0061] It can be understood that the units and modules involved in the embodiments of the present application can be implemented by software or hardware, for example, the units and modules can be located in a processor.

[0062] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0063] The present application provides a network status monitoring and optimization processing method, the working process of the method can be implemented by electronic devices, such as computers, handheld smart terminals, etc. For the convenience of explanation, the embodiments of the present application are described with the method execution subject as a computer.

[0064] Figure 1 A schematic diagram of a network status monitoring and optimization processing method provided in an embodiment of the present application, such as Figure 1 As shown, the present application provides a network status monitoring and optimization processing method. In some embodiments, the method includes S1-S4, which are as follows:

[0065] S1. Obtain network status parameters through monitoring;

[0066] Among them, network status parameters are a series of indicators used to describe network performance and health. The parameters are used to indicate the operation status of the network, diagnose problems, and optimize network performance.

[0067] S2. Determine data transmission parameters according to the network status parameters;

[0068] Among them, data transmission parameters refer to a series of performance indicators involved in transmitting data in the network, which are used to measure the efficiency and quality of data moving on the network.

[0069] In some embodiments, the network status parameters include network bandwidth and data packet transmission delay, and the data transmission parameters include transmission rate;

[0070] S2, including: determining a transmission rate according to network bandwidth and data packet transmission delay.

[0071] Specifically, the bandwidth (W) and data packet transmission delay (D) on the network link can be obtained by monitoring the network bandwidth and delay in real time.

[0072] Bandwidth refers to the amount of data that can be transmitted per unit time, usually in bps (bits per second), and usually varies from a few kbps to several Gbps. Its ideal state is the maximum physical transmission capacity of the network, and the optimal value is usually 70-80Mbps.

[0073] The packet transmission delay refers to the time difference between the sending end and the receiving end of the packet, which is usually measured in milliseconds (ms). The lower the better. The packet transmission delay ranges from 0 to 1000 milliseconds, and the optimal value is usually 50-100 milliseconds.

[0074] These two indicators comprehensively reflect the actual transmission capacity and performance of the current network. For example, in an actual application of a patrol control automation method based on Unicom intelligence, when the intelligent patrol device is sending the detection results to the central server, if the network bandwidth suddenly drops or the delay increases, W will decrease accordingly and D will increase.

[0075] In some embodiments, the transmission rate is determined by the following formula based on the network bandwidth and the data packet transmission delay:

[0076] R=W / (1+D)

[0077] Among them, W represents the network bandwidth, D represents the data packet transmission delay, and R represents the transmission rate.

[0078] In this step, the above formula defines a relationship that is proportional to the bandwidth and inversely proportional to the delay to calculate the optimal transmission rate R. The higher the bandwidth, the more data can be processed per unit time, so the transmission rate should be increased accordingly. When the delay increases, in order to avoid efficiency loss caused by congestion and retransmission, it is more reasonable to appropriately reduce the transmission rate. The denominator plus 1 in this formula is mainly to avoid the division by zero error that may occur when the delay is close to 0. At the same time, it can also have the effect of slightly smoothing the change in transmission rate, avoiding large-scale changes in transmission rate caused by slight delay fluctuations. The optimal transmission rate should be within the bandwidth allowed range, and maximize the transmission efficiency while ensuring that the data arrives in time.

[0079] The above settings can ensure that even when the network bandwidth is large but there is a high latency, the system can choose a more stable lower transmission rate to avoid packet loss or retransmission problems caused by latency. For example, if the network bandwidth is stable at 100Mbps during a certain period of time, and the latency suddenly increases from 10ms to 50ms, the new transmission rate calculated according to the above formula will be adjusted downward to reduce the error rate during data transmission.

[0080] By dividing the bandwidth by 1 plus the delay, this application can make full use of bandwidth resources when the network delay is low, and appropriately reduce the transmission rate when the network delay is high, thereby avoiding data packet loss or retransmission caused by excessive use of bandwidth. This setting method allows the transmission rate to flexibly adapt to changes in network conditions and improve transmission efficiency.

[0081] In some embodiments, the network status parameters include packet loss rate and network delay, and the data transmission parameters include retransmission interval, number of retransmissions and data fragment size;

[0082] S2, including: determining the retransmission interval and the number of retransmissions of the data transmission protocol according to the packet loss rate and the network delay, and dynamically adjusting the data segment size.

[0083] This step specifically includes: monitoring the packet loss rate and network delay of the current network; adjusting the retransmission interval and number of retransmissions of the data transmission protocol according to the monitoring results; dynamically adjusting the data segment size to reduce packet loss caused by large packet transmission; and gradually restoring the default data transmission parameter settings when the network status returns to stability.

[0084] First, monitor the current network packet loss rate and network latency. This step involves obtaining real-time packet loss rate and latency information during network communication through network monitoring tools or algorithms. This can be achieved by deploying sensors or monitoring points at key nodes in the data transmission path to capture and record the sending and receiving of data packets. This information is crucial for subsequent parameter adjustments to ensure the rationality and effectiveness of the transmission strategy.

[0085] The retransmission interval and retransmission times of the data transmission protocol are adjusted according to the monitoring results. Specifically, when a high packet loss rate and network delay are detected in the network, the retransmission interval needs to be reduced and the retransmission times need to be increased so as to detect and recover lost data packets more quickly and improve the reliability and efficiency of data transmission. For example, in one embodiment, if the packet loss rate reaches 10%, the system can adjust the retransmission interval from 1 second to 0.5 seconds and increase the retransmission times from 3 times to 5 times.

[0086] In some embodiments, determining the retransmission interval and the number of retransmissions of the data transmission protocol according to the packet loss rate and the network delay includes:

[0087] Determine the adjustment factor based on the packet loss rate and network delay;

[0088] When the adjustment factor is greater than the first preset threshold, the retransmission interval is increased, and when the adjustment factor is less than or equal to the first preset threshold, the retransmission interval is kept unchanged;

[0089] When the adjustment factor is greater than the second preset threshold, the number of retransmissions is increased, and when the adjustment factor is less than or equal to the second preset threshold, the number of retransmissions is kept unchanged;

[0090] The second preset threshold is greater than the first preset threshold.

[0091] In some embodiments, based on the packet loss rate and the network delay, the adjustment factor is determined by the following formula:

[0092] K=P×T / C

[0093] Among them, P represents the packet loss rate, T represents the network delay, K represents the adjustment factor, and C is a constant representing the reference value.

[0094] Specifically, the above process aims to dynamically adjust the parameters of the data transmission protocol through real-time monitoring of network conditions to ensure the efficiency and reliability of data transmission. Specifically, the adjustment factor K is calculated based on the packet loss rate P and the network delay T. The packet loss rate P represents the proportion of data packets lost during network transmission, usually between 0 and 1. The network delay T represents the time required from sending to receiving, usually in milliseconds. C is a constant, representing a benchmark value for evaluating the overall stability of the network. The specific value of this constant depends on the network environment and application requirements. It is generally set in the range of 1 to 1000, and the optimal value needs to be determined based on actual conditions. The purpose of the calculation formula K = P × T / C is to comprehensively consider the impact of packet loss rate and network delay on network transmission, and generate a quantitative indicator K for subsequent decision-making.

[0095] If the calculated K is greater than the first preset threshold Th1, the system will increase the retransmission interval Tc1. This is because in the case of a high packet loss rate and a large network delay, frequent retransmissions may increase the network burden, so appropriately extending the retransmission interval can reduce network pressure and improve transmission efficiency. If K is less than or equal to Th1, it means that the network condition is acceptable and there is no need to change the existing retransmission interval to maintain the current performance level.

[0096] In addition, if K is greater than the second preset threshold Th2, it indicates that the network condition is poor and the number of retransmissions Rc1 needs to be increased to ensure that the data can be successfully transmitted. On the contrary, if K is less than or equal to Th2, the number of retransmissions remains unchanged to avoid unnecessary retransmissions and waste of resources. Generally, the value of Th2 is higher than Th1, reflecting a stricter standard and applicable to more severe network environments.

[0097] Finally, after each adjustment, the change records of the retransmission interval and the number of retransmissions will be stored in the system log for subsequent analysis and debugging. This helps to track historical data, optimize algorithm parameters, and improve the overall performance of the system.

[0098] For example, in a specific embodiment, a patrol robot of a power company is receiving instructions through a remote network to perform operations. Assume that the monitoring data shows that the current network packet loss rate is 0.1, the network delay is 100 milliseconds, and the reference value C is set to 500. The calculated adjustment factor K is (0.1*100) / 500=0.02. The system preset threshold Th1 is 0.1, and Th2 is 0.5. Since K (0.02) is less than Th1, the system decides not to adjust the retransmission interval, and K is much smaller than Th2, and it also decides to keep the number of retransmissions unchanged. However, if the network condition deteriorates, the packet loss rate rises to 0.2, and the network delay increases to 200 milliseconds, then the new K value is (0.2*200) / 500=0.08. At this time, K is greater than Th1 but less than Th2, the system will increase the retransmission interval, but still keep the number of retransmissions unchanged, until the network condition further deteriorates to K exceeds Th2, the number of retransmissions will be increased. Through this dynamic adjustment mechanism, the system can maintain efficient patrol control in various network environments.

[0099] In some embodiments, the step of calculating the adjustment factor K based on the packet loss rate P and the network delay T further comprises the following steps:

[0100] Initialize the initial values ​​P0 and T0 of the packet loss rate P and network delay T;

[0101] Obtain the current packet loss rate P and network delay T in real time;

[0102] The calculation is performed using the formula K = (P-P0) × (T-T0) / C, where C is a constant representing a benchmark value used to measure network stability;

[0103] When K is greater than the third preset threshold Th3, the retransmission interval Tc2 is further increased; when K is less than or equal to the threshold Th3, the original retransmission interval is restored.

[0104] Initialize the initial values ​​P0 and T0 of the packet loss rate P and network delay T. This step is to determine a baseline performance indicator before starting the system operation so that there is a reference value in the subsequent operation process. The initial values ​​P0 and T0 are usually the packet loss rate and network delay of the system under the best network conditions, or the average value of historical data. These initial values ​​can ensure a reliable comparison standard in a dynamically changing network environment.

[0105] Get the current packet loss rate P and network delay T in real time. This step is to monitor the actual performance of the current network. The packet loss rate P reflects the proportion of data packets lost during network transmission, while the network delay T reflects the time it takes for data to travel from the sender to the receiver. These real-time data are obtained through network monitoring tools or sensors to ensure that the system can respond quickly to changes in network status.

[0106] The formula K = (P-P0) × (T-T0) / C is used for calculation, where C is a constant, representing a benchmark value, which is used to measure network stability. P0 and T0 in the formula are the initial values ​​in the previous step, and P and T are the current real-time data. The constant C is a predetermined benchmark value, usually ranging from 0.1 to 1. The optimal value can be selected according to different network environments and requirements. The formula is designed to comprehensively consider the impact of two key indicators, packet loss rate and network delay, on network performance. If the value of K is large, it means that the current network environment has deteriorated significantly compared to the initial state; otherwise, it means that the network performance is stable or slightly improved.

[0107] When K is greater than the threshold Th3, the retransmission interval Tc2 is further increased. When K is less than or equal to the threshold Th3, the original retransmission interval is restored. Threshold Th3 is a limit used to determine whether the current network status needs to be adjusted, and is usually set to a reasonable positive value. If K is greater than Th3, it means that the network condition is poor and the retransmission interval Tc2 needs to be increased to reduce unnecessary network congestion. On the contrary, if K is less than or equal to Th3, it means that the network condition is good and there is no need to adjust the retransmission interval, thereby restoring the original transmission efficiency. This mechanism ensures that the system automatically adapts when network conditions deteriorate, and resumes normal operation when conditions improve, thereby improving the reliability and performance of the overall system.

[0108] For example, in one embodiment, a certain intelligent inspection and control system measures a packet loss rate P0 of 0.1% and a network delay T0 of 20 milliseconds in the initial state. Through real-time monitoring, the system finds that the current packet loss rate P rises to 0.3% and the network delay T increases to 50 milliseconds. Using the above formula, the K value is calculated to be (0.3%-0.1%)×(50ms-20ms) / 0.5=2. Assuming that the threshold Th3 is set to 1, since the K value is greater than 1, the system will increase the retransmission interval Tc2 to avoid network congestion. In another scenario, if the packet loss rate drops to 0.1% and the network delay remains at 20 milliseconds, the calculated K value is 0, which is less than the threshold Th3. The system will restore the original retransmission interval to ensure efficient communication efficiency.

[0109] In some embodiments, the initializing the initial values ​​P0 and T0 of the packet loss rate P and the network delay T further comprises the following steps:

[0110] When the system starts, the packet loss rate and network delay of the first monitoring are recorded and set as P0 and T0;

[0111] Regularly re-evaluate and update the initial values ​​P0 and T0, with the evaluation period set to 10 minutes;

[0112] When the changes of P0 and T0 exceed a certain threshold D, reinitialize P0 and T0;

[0113] The updated P0 and T0 will be used for the subsequent calculation of the adjustment factor K.

[0114] When the system starts, the first monitored packet loss rate and network delay are recorded and set as P0 and T0. This is to establish a baseline value for subsequent comparison and adjustment. For example, during the startup of the network monitoring system, the first recorded packet loss rate is 0.05% and the network delay is 20 milliseconds. These two values ​​are set as P0 and T0.

[0115] The initial values ​​P0 and T0 are re-evaluated and updated regularly, and the evaluation period is set to 10 minutes. This step is to ensure that the initial values ​​can reflect the latest status of the network and prevent the benchmark values ​​from becoming invalid due to changes in the network environment. In one embodiment, the system monitors the packet loss rate and network delay of the network again every 10 minutes. If the new packet loss rate is 0.06% and the network delay is 22 milliseconds, P0 and T0 are updated to these new values.

[0116] When the changes in P0 and T0 exceed a certain threshold D, P0 and T0 are reinitialized. The purpose of this step is to reset the benchmark value in time when the network conditions change significantly, to avoid inaccurate subsequent calculation results due to incorrect benchmarks. Threshold D can be set according to the specific application scenario. The common range is that the packet loss rate changes by more than 0.1% and the network delay changes by more than 5 milliseconds. Specifically, if after multiple 10-minute evaluations, it is found that the packet loss rate has increased from 0.05% to 0.16%, exceeding the threshold of 0.1%, it will trigger reinitialization and reset P0 and T0 to the currently monitored packet loss rate and network delay.

[0117] The updated P0 and T0 will be used for the subsequent calculation of the adjustment factor K. The adjustment factor K is a weight value calculated based on P0 and T0, and is used to adjust the optimization strategy of network performance. Specifically, assume that the calculation formula of K is:

[0118] K=alpha×times P+beta×times T

[0119] Among them, alpha and beta are the weight coefficients of packet loss rate and network delay respectively, ranging from 0 to 1, and alpha + beta = 1. The optimal value is usually adjusted according to the actual application effect. For example, if you pay more attention to the packet loss rate, alpha can be set to 0.7 and beta can be set to 0.3.

[0120] The meaning of this formula is that when calculating the adjustment factor K, both the impact of packet loss rate on network performance and the impact of network delay should be considered, and the weight coefficient reflects the importance of both. The formula set in this way can enable the system to flexibly adjust the network optimization strategy in different situations and improve the overall performance.

[0121] Optionally, when the changes of P0 and T0 exceed a certain threshold D, reinitializing P0 and T0 further includes:

[0122] Monitor the changes of P0 and T0;

[0123] Use the formula |(P0_new-P0_old) / P0_old|>D and |(T0_new-T0_old) / T0_old|>D to judge the change range, where P0_new and T0_new are new measurement values, P0_old and T0_old are old measurement values, and D is the threshold value used to judge whether the change range is too large;

[0124] When any of the conditions is met, the values ​​of P0 and T0 are re-recorded; the system-related parameters are reset to adapt to the new network status.

[0125] First, monitor the changes in P0 and T0. This process involves regularly collecting the current pressure (P0) and temperature (T0) values ​​of the system and comparing these new measurements with the old measurements stored previously. Through continuous monitoring, the changing trends of these two key parameters can be obtained in real time, and any abnormal fluctuations can be discovered in time.

[0126] Secondly, use the formula |(P0_new-P0_old) / P0_old|>D and |(T0_new-T0_old) / T0_old|>D to judge the change range. Here, P0_new and T0_new are the latest measured values, P0_old and T0_old are the last recorded measured values, and D is the preset threshold. The threshold D is usually set between 0.1 and 0.3, and the specific value is optimized according to the needs and stability requirements of the system. This formula represents the rate of change of the current measured value relative to the old measured value. When the rate of change exceeds the threshold D, it indicates that the system state has changed significantly and corresponding measures need to be taken.

[0127] When any of the above conditions is met, that is, when the rate of change of P0 or T0 exceeds the threshold D, the system will automatically re-record the new values ​​of P0 and T0. This step ensures that the system's measurement data is always up to date and reflects the current system status.

[0128] Finally, the system-related parameters are reset to adapt to the new network status. After the system re-records the values ​​of P0 and T0, it will adjust the relevant control parameters and algorithms based on these new measurement results so that the system can better cope with the new working environment. For example, in one embodiment, if it is detected that the pressure P0 suddenly increases by 10% and exceeds the preset threshold D (e.g., 0.2), the system will re-record the new pressure value and adjust the operating frequency of the pump and the valve opening to maintain the stable operation of the pipeline network.

[0129] Among them, the use of formulas |(P0_new-P0_old) / P0_old|>D and |(T0_new-T0_old) / T0_old|>D to judge the change amplitude further includes the following steps: obtaining the latest packet loss rate P0_new and network delay T0_new in real time; comparing with P0_old and T0_old in historical records; when |(P0_new-P0_old) / P0_old|>D is established, triggering the reinitialization of P0; when |(T0_new-T0_old) / T0_old|>D is established, triggering the reinitialization of T0.

[0130] Real-time acquisition of the latest packet loss rate P0_new and network delay T0_new means that during system operation, the current packet loss rate P0_new and network delay T0_new are collected in real time by monitoring the network status. These two parameters reflect the quality of the current network environment and are crucial for timely discovery and handling of network problems.

[0131] Comparison with P0_old and T0_old in historical records refers to comparing the currently collected packet loss rate P0_new and network delay T0_new with the previously recorded historical data P0_old and T0_old, respectively. This process is usually completed automatically by the background system to detect changes in network performance.

[0132] When |(P0_new-P0_old) / P0_old|>D holds, triggering the reinitialization of P0 means that when the change in the current packet loss rate P0_new and the historical packet loss rate P0_old exceeds the preset threshold D, the system will reinitialize the packet loss rate parameter. The value range of parameter D is generally 0 to 1, and the optimal value depends on the specific application scenario. Usually, D can be set to 0.1 or 0.2, indicating a change of 10% or 20%. The purpose of this formula is to adjust the relevant parameters in a timely manner when the packet loss rate changes significantly to ensure that the system can quickly adapt to new network conditions.

[0133] When |(T0_new-T0_old) / T0_old|>D holds, triggering the reinitialization of T0 also means that when the change between the current network delay T0_new and the historical network delay T0_old exceeds the preset threshold D, the system will reinitialize the network delay parameters. The value and optimization principle of D are the same as the previous formula. The purpose of setting the formula is to ensure that when the network delay changes significantly, the system can respond quickly and adjust the corresponding control strategy to avoid the impact of network problems on the overall service quality.

[0134] For example, in one embodiment, assume that the monitoring system of a certain Unicom intelligent system updates the packet loss rate and network delay data once a minute. At a certain moment, the current packet loss rate is 2%, and the historical packet loss rate is 1%, that is, P0_new = 0.02, P0_old = 0.01. Calculate |(P0_new-P0_old) / P0_old| = |(0.02-0.01) / 0.01| = 1, which exceeds the preset threshold D = 0.1. At this time, the system will trigger the reinitialization of P0, re-collect and adjust the packet loss rate parameters. This helps the system respond to network changes in a timely manner and ensure service quality. Similarly, if the current network delay is 100 milliseconds and the historical network delay is 80 milliseconds, that is, T0_new=100, T0_old=80, the calculation |(T0_new-T0_old) / T0_old|=|(100-80) / 80|=0.25, which also exceeds the threshold D=0.2, the system will reinitialize T0 to ensure that the network delay parameters are consistent with the actual network conditions. Through such a mechanism, the system can respond quickly when the network conditions change, ensuring the automation and efficiency of the inspection control.

[0135] In this application, the packet loss caused by large packet transmission is reduced by dynamically adjusting the data fragment size. When the network quality is poor, large packets are more likely to be lost, so it is necessary to split the large data packet into smaller data packets for transmission, thereby reducing the probability of transmission failure of a single data packet. For example, if the monitored network delay exceeds 50 milliseconds, the size of the data packet can be adjusted from 1024 bytes to 512 bytes.

[0136] In some embodiments, the data shard size is dynamically adjusted by the following formula:

[0137] data_packet_size

[0138] =max(default_packet_size-delay_factor

[0139] ×delay,min_packet_size)

[0140] Among them, default_packet_size is the default packet size (for example, 1024 bytes), delay is the network delay (unit: milliseconds), min_packet_size is the minimum packet size (for example, 512 bytes), and delay_factor is the delay adjustment factor (for example, 1 byte / millisecond). This formula ensures that the packet size can be effectively reduced when the network delay is high, but it is still not less than the minimum value.

[0141] When the network status returns to stability, gradually restore the default data transmission parameter settings. This step ensures that after the network conditions improve, the system can gradually fall back to the initial optimization parameters to avoid wasting resources due to over-conservatism. For example, when the packet loss rate drops to 2% and the delay is less than 30 milliseconds, the system can gradually restore the data packet size to 1024 bytes per minute and gradually increase the retransmission interval from 0.5 seconds to 1 second, and finally restore the default settings to ensure the best transmission effect after the network returns to stability.

[0142] S3. Determine the transmission priority of the target data according to the importance and real-time requirements of the target data to be transmitted;

[0143] In some embodiments, in S3, according to the importance and real-time requirements of the target data to be transmitted, the transmission priority of the target data is determined by the following formula:

[0144] P=(Q+V) / 2

[0145] Among them, P represents the transmission priority, Q represents the importance requirement of the target data, and V represents the real-time requirement of the target data.

[0146] Specifically, in a multi-task environment, different data have different requirements for timeliness and importance. This step ensures that critical data is transmitted first by dynamically allocating transmission priority P.

[0147] Among them, the importance requirement Q reflects the relative value or urgency of the information, and the larger the value, the more important it is; the real-time requirement V indicates the urgency of the information to be conveyed quickly, and the larger the value, the higher the requirement.

[0148] The purpose of the above transmission priority calculation formula is to combine these two attributes to assess the priority of data transmission, so that those data that are both important and urgently needed are given priority. The priority P value is calculated using the two-factor average method, ensuring that both the importance of the content and the actual time constraints are not ignored.

[0149] In some examples, Q generally ranges from 1 to 5, with the higher the value, the more important the data is; V is also between 1 and 5, reflecting the strictness of the arrival time of the batch of data. The two are summed up and averaged to obtain a comprehensive index P between 1 and 5, which indicates the position level that the current task should occupy in the queue of all tasks to be executed. For example, suppose the inspection robot captures an image of an obvious pipeline leak. This information is high-priority content (assuming Q = 4), and in order to promptly warn of potential risk accidents, it needs to be transmitted immediately (V = 5), then P is (4 + 5) / 2 = 4.5, indicating that this information should be uploaded and processed as soon as possible.

[0150] In some examples, the Q value range can also be set from 0 to 10, and the Q value of important data is usually above 8; the V value range can also be set from 0 to 10, and the V value of data with high real-time requirements is above 8. The new transmission priority P is obtained by calculating (P = (Q + V) / 2). The purpose of this formula is to balance the importance of data and real-time requirements to ensure that high-priority data can be transmitted in a timely manner. For example, if the data of a surveillance camera is not only important but also needs to be transmitted in real time, Q and V are both set to 9, so that P is calculated to be 9, indicating that the data of the camera has a high transmission priority.

[0151] In some examples, the value range of Q and V can also be set between 0 and 1, with 1 representing the highest importance or the most urgent. The calculation formula of the priority P is P = (Q + V) / 2, that is, the average value of the data Q and V is taken as the priority. This ensures that highly important and urgent tasks can get higher priority and be processed more quickly.

[0152] In the present application, determining the transmission priority of the target data may include the following steps:

[0153] S31. Collect data importance and real-time information at preset time intervals;

[0154] Specifically, the importance and real-time information of data are collected at preset time intervals to ensure that the system can dynamically adjust the transmission priority according to the latest situation. The preset time interval can be flexibly set according to the needs of the application scenario. For example, the importance and real-time information of data can be collected immediately when the inspection robot detects an abnormality, or once every minute.

[0155] S32. Calculate the importance requirement Q and real-time requirement V for each piece of data;

[0156] Specifically, the importance requirement Q and real-time requirement V of each piece of data are calculated. This step aims to conduct a detailed analysis of each piece of data to determine its importance and timeliness during the transmission process. The importance requirement Q reflects the importance of the data in the overall inspection task, which can usually be expressed on a scale of 0 to 10, with 10 being the most important; the real-time requirement V reflects how quickly the data needs to be transmitted and processed, which can also be expressed on a scale of 0 to 10, with 10 being the highest real-time requirement.

[0157] S33. Calculate the transmission priority P using the formula P = (Q + V) / 2, where P is the transmission priority, Q is the importance of the data, and V is the real-time requirement of the data;

[0158] Specifically, P is calculated by taking the average of Q and V, which can balance the importance and real-time nature of the data and avoid the impact of extreme situations in one aspect on the overall transmission priority. This setting ensures that both the importance of the data and the real-time requirements are taken into account during the transmission process.

[0159] In the present application, by dynamically allocating the transmission priority P, the dynamic adjustment of the transmission priority can better adapt to the ever-changing network environment and ensure the efficiency and stability of data transmission.

[0160] S4. Based on the data transmission parameters and the transmission priority, adopt a target path to perform data transmission on the target data, wherein the target path is a preset main path or a backup path with the highest stability when the preset main path is unavailable.

[0161] In some embodiments, in S4, the backup path with the highest stability when the preset main path is unavailable is determined by the following formula:

[0162] S = min(Pi,Ci),

[0163] Wherein, S represents the backup path with the highest stability when the preset main path is unavailable, Pi represents the priority of the i-th transmission path, and Ci represents the stability of the i-th transmission path.

[0164] Specifically, in the case of network instability, the backup transmission path S is automatically enabled, S = min (Pi, Ci), where Pi is the priority of the i-th transmission path, and Ci is the stability of the i-th transmission path. This strategy is a set of alternative plans that are activated when the main transmission route is unavailable or inefficient, ensuring that the alternative line is quickly enabled when the main communication channel fails. The priority Pi of the path is comprehensively evaluated according to the aforementioned method, and the stability Ci evaluates the ability of a specific line to resist sudden failures and the ability to perform continuously and stably, usually between 0 and 1. The closer the value is to 1, the more robust and reliable it is. The formula selects the lower of the two path scores as the final judgment criterion, intending to ensure that even in the face of multiple candidate routes, the system can still select the best replacement option that is both suitable and stable.

[0165] For example, when severe jitter is detected in the original transmission channel, the algorithm quickly calculates the relevant parameters of all existing alternative paths, and selects the most suitable backup path for data relay based on the minimum principle, ensuring that the overall communication will not be interrupted and the normal operation of the entire system is maintained. Specifically, during the remote operation of an inspection robot, if it is found that the main channel has an increased risk of signal interruption due to high interference signal strength, the mechanism can immediately call another backup link to continue transmitting important data collected by the robot, ensuring the smooth progress of the inspection work.

[0166] In a specific embodiment, if the trunk line is interrupted due to weather factors, the control system will make a judgment among the two remaining available paths: one has a slightly lower priority (P2=3) but has been proven to be extremely stable after multiple tests (C2=0.9); the other has a higher priority (P3=4) but has frequent problems (C3=0.6), so the system will eventually choose the first line as the emergency channel to continue data transmission.

[0167] For example, during an intelligent inspection, if the current transmission path is found to have a lower priority due to temporary network fluctuations, and the backup path S has a higher priority than the current path and has good stability, the system will automatically switch to the backup path to ensure the quality and reliability of data transmission. This automatic switching mechanism helps improve the robustness of the overall system and user experience.

[0168] For another example, in an application scenario of an inspection control automation method based on Unicom Intelligence, suppose there is an inspection robot that is performing equipment inspections. It collects the importance and real-time information of the detected data every minute. At a certain moment, the robot detects that a temperature sensor data is abnormal (importance requirement Q=9), and the data needs to be immediately transmitted to the central control center for further analysis (real-time requirement V=8). According to the formula P=(Q+V) / 2, the transmission priority of the data is calculated to be P=(9+8) / 2=8.5. Then, the robot has three available transmission paths: path 1 has priority Pi1=9 and stability Ci1=7; path 2 has priority Pi2=8 and stability Ci2=8; path 3 has priority Pi3=7 and stability Ci3=9. According to the formula S=min(Pi,Ci), the S values ​​of each path are calculated as S1=min(9,7)=7, S2=min(8,8)=8, and S3=min(7,9)=7. Finally, the system will select either path 1 or path 3, because the S values ​​of both paths are 7, which meets the stability requirements of the transmission path. This choice ensures that important data can be delivered quickly and the reliability of the data can be guaranteed during the transmission process.

[0169] For another example, suppose there are three transmission paths in the patrol control automation system, path A has a priority of 0.7 and a stability of 0.6; path B has a priority of 0.8 and a stability of 0.8; path C has a priority of 0.6 and a stability of 0.9, then the score of path A is 0.6, the score of path B is 0.8, and the score of path C is 0.6. Therefore, path B is selected as the best transmission path.

[0170] In one embodiment, it is assumed that the inspection robot of a power company needs to transmit the detected power grid abnormality information back to the command center in real time. The system finds through real-time monitoring that the current network bandwidth is 10Mbps and the delay is 50ms. Then, according to R=W / (1+D), the current transmission rate is calculated to be about 6.7Mbps. Assume that there are two tasks at this time: Task 1 is used to transmit important but not urgent environmental monitoring data, and its data Q and V are both 0.5, so the priority P=(0.5+0.5) / 2=0.5; Task 2 is used to transmit urgent and important abnormal alarm data, and its data Q and V are both 0.9, so the priority P=(0.9+0.9) / 2=0.9. When selecting the transmission path, considering the actual performance of paths A, B, and C and the evaluation method mentioned above, path B is finally selected as the optimal path to transmit the abnormal alarm data of task 2, ensuring that the alarm data can be accurately transmitted at the fastest speed.

[0171] In one embodiment, assume that an automated inspection system needs to send instructions from a central server to multiple remote devices. The system regularly collects Q and V data. Assuming that Q=0.8 and V=0.9 at a certain moment, P=(0.8+0.9) / 2=0.85 is calculated. At the same time, during the transmission process, the system detects the network quality W=0.9 and the network delay D=0.1 of the current path, and calculates R=0.9- / (1+0.1)=0.818. The system continues to detect path stability, assuming that Pi=0.85 and Ci=0.8 of path 1, and Pi=0.9 and Ci=0.7 of path 2, and finally selects path S1=min(0.85,0.8)=0.8, because path 1 has higher stability and is more suitable as a transmission path.

[0172] In this step, when switching paths, the minimum value of priority and stability is selected as the final path selection basis, ensuring that not only the priority but also the stability of the path is considered when selecting a path, thereby improving the reliability of the overall transmission.

[0173] In summary, the method of the present application can not only adjust parameters in real time according to network conditions, but also optimize the data transmission process according to different business needs, and has the ability to flexibly respond to unexpected situations, significantly improving data communication quality and user experience.

[0174] In addition, there are other problems with existing inspection technologies, specifically: under unstable network conditions, the loss of data packets may cause the interruption of inspection tasks; secondly, when multiple devices are online at the same time, resource preemption may cause delays in inspection scheduling; thirdly, in scenarios with frequent environmental changes, the accuracy of sensors may decrease, thereby causing errors in inspection data; in addition, in the event of sudden abnormal events, the system response speed may lag due to the imperfect processing mechanism; finally, when a large amount of data needs to be processed, the high complexity of the algorithm may lead to excessive occupation of computing resources.

[0175] Based on the above problems, this application also provides a patrol control automation method based on Unicom intelligence. This method aims to solve patrol problems in situations such as network instability, multi-device resource competition, frequent environmental changes, sudden abnormal events and large amounts of data processing through a series of intelligent technologies and algorithm optimization.

[0176] Figure 2 A schematic diagram of a network status monitoring and optimization processing method provided in an embodiment of the present application, such as Figure 2 As shown, the present application provides an automated inspection control method based on Unicom intelligence, including:

[0177] (1) Dynamically adjust data transmission parameters based on real-time network status monitoring mechanism to reduce packet loss and inspection task interruption.

[0178] The key to this step is to monitor the network status in real time, including but not limited to signal strength, bandwidth utilization, and data transmission success rate. When the network status is detected to be poor, the system will automatically adjust the transmission parameters such as data packet size and number of retransmissions to ensure reliable data transmission. For example, in one embodiment, the inspection robot suddenly encounters a situation where the wireless signal is attenuated while performing a task. At this time, the real-time network status monitoring system detects that the signal strength is lower than the threshold, and then starts the adaptive transmission mechanism, reducing the data packet size from the original 1024 bytes to 256 bytes, and increasing the number of data retransmissions to 5 times, thereby effectively avoiding data packet loss and ensuring the continuity of the inspection task.

[0179] (2) Optimize the inspection task scheduling strategy based on the multi-device resource demand prediction model to avoid inspection scheduling delays caused by resource preemption.

[0180] This step involves establishing a multi-device resource demand prediction model by analyzing the historical task data and resource consumption patterns of each inspection device. Based on this model, the system can predict the peak resource demand period in advance and dynamically adjust the execution order and allocation priority of inspection tasks. Specifically, suppose that in an intelligent factory, multiple inspection robots need to inspect different areas at the same time. Through the multi-device resource demand prediction model, the system finds that the access demand for certain specific areas is concentrated within a certain period of time, and immediately reallocates tasks to allow some robots to complete the inspection of low resource competition areas first, thereby effectively alleviating the inspection delay problem caused by resource preemption.

[0181] (3) The sensor data is corrected in real time through an adaptive calibration algorithm to improve the accuracy of inspection data under conditions of frequent environmental changes.

[0182] The core of this step is to detect and correct the accuracy deviation of the sensor caused by changes in environmental factors such as temperature and humidity in real time during the inspection process. The adaptive calibration algorithm ensures that the collected data is accurate and reliable by continuously comparing and correcting the sensor data. For example, in one embodiment, when an inspection robot equipped with a temperature and humidity sensor enters a high temperature and high humidity area, the sensor reading is offset. At this time, the adaptive calibration algorithm is immediately started, comparing the current reading with the historical normal data, and adjusting the calibration parameters of the sensor in real time to restore the temperature and humidity readings to the standard range, thereby improving the accuracy of the inspection data.

[0183] (4) Build a rapid response system for abnormal events to improve the response speed to emergencies during inspections.

[0184] The purpose of this step is to establish an intelligent monitoring and alarm system to quickly trigger preset emergency measures after detecting an abnormal event. The system will automatically respond in a graded manner according to the severity of the abnormal event and call the corresponding processing module. In a specific embodiment, a patrol robot discovered a leakage fault in a production equipment during the patrol process. The abnormal event rapid response system immediately detected this situation, triggered an alarm and generated an emergency processing work order, notifying maintenance personnel to rush to the scene for processing as soon as possible, greatly shortening the accident processing time and reducing potential risks.

[0185] (5) Use lightweight machine learning models for data processing to reduce algorithm complexity and computing resource usage.

[0186] This step achieves rapid data processing and analysis by selecting or designing an efficient, lightweight machine learning model suitable for inspection data processing. Lightweight models not only maintain high accuracy, but also significantly reduce the consumption of computing resources. For example, in a large-scale inspection project, the system needs to process a large amount of data reported by thousands of inspection devices every day. By introducing lightweight machine learning models, the system's computing efficiency is greatly improved, the processing time is shortened from several hours to tens of minutes, and the computing resource occupancy rate is significantly reduced, ensuring the continuous and stable operation of the system.

[0187] In summary, an automated inspection control method based on Unicom intelligence effectively solves inspection problems in situations such as network instability, multi-device resource competition, frequent environmental changes, sudden abnormal events, and large amounts of data processing through the above five core steps, providing a strong guarantee for the efficiency, stability, and accuracy of intelligent inspections.

[0188] It should be understood that, although the various steps in the flowcharts in the above-described embodiments are sequentially displayed according to the indications of the arrows, these steps are not necessarily executed sequentially in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps is not strictly limited in order, and they can be executed in other orders. Moreover, at least a portion of the steps in the figure may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily to be carried out sequentially, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0189] Figure 3 A schematic diagram of a network status monitoring and optimization processing device provided in an embodiment of the present application, such as Figure 3 As shown, the present application provides a network status monitoring and optimization processing device, the device comprising:

[0190] A parameter acquisition module 11, which is configured to acquire network status parameters through monitoring;

[0191] A parameter determination module 12, configured to determine a data transmission parameter according to the network status parameter;

[0192] A priority determination module 13, which is configured to determine the transmission priority of the target data according to the importance requirement and real-time requirement of the target data to be transmitted;

[0193] The data transmission module 14 is configured to transmit the target data using a target path based on the data transmission parameters and the transmission priority, wherein the target path is a preset main path or a backup path with the highest stability when the preset main path is unavailable.

[0194] Regarding the limitation of the network status monitoring and optimization processing device, reference may be made to the limitation of the network status monitoring and optimization processing method in the above-mentioned embodiments of the present application, which will not be repeated in this embodiment.

[0195] Figure 4 Another schematic diagram of the network status monitoring and optimization processing device provided in the embodiment of the present application is as follows Figure 4 As shown, in some embodiments, the present application provides a network status monitoring and optimization processing device, including a memory 22 and a processor 21, the memory stores a computer program, and the processor is configured to run the computer program to execute the network status monitoring and optimization processing method in the above-mentioned embodiments of the present application.

[0196] The memory is connected to the processor, the memory may be a flash memory or a read-only memory or other memory, and the processor may be a central processing unit or a single-chip microcomputer.

[0197] In some embodiments, the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the network status monitoring and optimization processing methods in the above-mentioned embodiments of the present application are implemented.

[0198] The computer-readable storage medium includes volatile or non-volatile, removable or non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, computer program modules or other data). Computer-readable storage media include, but are not limited to, RAM (Random Access Memory), ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable read only memory), flash memory or other memory technology, CD-ROM (Compact Disc Read-Only Memory), digital versatile disk (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer.

[0199] It is to be understood that the above embodiments are merely exemplary embodiments used to illustrate the principles of the present application, but the present application is not limited thereto. For those skilled in the art, various modifications and improvements can be made without departing from the spirit and substance of the present application, and these modifications and improvements are also considered to be within the scope of protection of the present application.

Claims

1. A network status monitoring and optimization processing method, characterized in that: The method comprises: S1. Obtain network status parameters through monitoring; S2. Determine data transmission parameters according to the network status parameters; S3. Determine the transmission priority of the target data according to the importance and real-time requirements of the target data to be transmitted; S4. Based on the data transmission parameters and the transmission priority, adopt a target path to perform data transmission on the target data, wherein the target path is a preset main path or a backup path with the highest stability when the preset main path is unavailable.

2. The network status monitoring and optimization processing method according to claim 1 is characterized in that: The network status parameters include network bandwidth and data packet transmission delay, and the data transmission parameters include transmission rate; S2, including: The transmission rate is determined based on the network bandwidth and data packet transmission delay.

3. The network status monitoring and optimization processing method according to claim 2 is characterized in that: Based on the network bandwidth and data packet transmission delay, the transmission rate is determined by the following formula: R=W / (1+D) Among them, W represents the network bandwidth, D represents the data packet transmission delay, and R represents the transmission rate.

4. The network status monitoring and optimization processing method according to claim 1 is characterized in that: The network status parameters include packet loss rate and network delay, and the data transmission parameters include retransmission interval, number of retransmissions and data fragment size; S2, including: The retransmission interval and number of retransmissions of the data transmission protocol are determined according to the packet loss rate and network delay, and the data segment size is dynamically adjusted.

5. The network status monitoring and optimization processing method according to claim 4 is characterized in that: Determine the retransmission interval and number of retransmissions of the data transmission protocol based on the packet loss rate and network delay, including: Determine the adjustment factor based on the packet loss rate and network delay; When the adjustment factor is greater than the first preset threshold, the retransmission interval is increased, and when the adjustment factor is less than or equal to the first preset threshold, the retransmission interval is kept unchanged; When the adjustment factor is greater than the second preset threshold, the number of retransmissions is increased, and when the adjustment factor is less than or equal to the second preset threshold, the number of retransmissions is kept unchanged; The second preset threshold is greater than the first preset threshold.

6. The network status monitoring and optimization processing method according to claim 5 is characterized in that: Based on the packet loss rate and network delay, the adjustment factor is determined by the following formula: K=P×T / C Among them, P represents the packet loss rate, T represents the network delay, K represents the adjustment factor, and C is a constant representing the reference value.

7. The network status monitoring and optimization processing method according to claim 4 is characterized in that: The data shard size is adjusted dynamically using the following formula: data_packet_size=max(default_packet_size-delay_factor×delay,min_packet_size) Among them, data_packet_size indicates the data fragment size, default_packet_size indicates the default data packet size, delay is the network delay, min_packet_size is the minimum data packet size, and delay_factor is the delay adjustment factor.

8. The network status monitoring and optimization processing method according to any one of claims 1 to 7, characterized in that: In S3, according to the importance and real-time requirements of the target data to be transmitted, the transmission priority of the target data is determined by the following formula: P=(Q+V) / 2 Among them, P represents the transmission priority, Q represents the importance requirement of the target data, and V represents the real-time requirement of the target data.

9. The network status monitoring and optimization processing method according to any one of claims 1 to 7, characterized in that: In S4, when the preset main path is unavailable, the backup path with the highest stability is determined by the following formula: S = min(Pi,Ci), Wherein, S represents the backup path with the highest stability when the preset main path is unavailable, Pi represents the priority of the i-th transmission path, and Ci represents the stability of the i-th transmission path.

10. A network status monitoring and optimization processing device, characterized in that: The device comprises: A parameter acquisition module, which is configured to acquire network status parameters through monitoring; a parameter determination module, configured to determine a data transmission parameter according to the network status parameter; A priority determination module, configured to determine the transmission priority of the target data to be transmitted according to the importance requirement and real-time requirement of the target data to be transmitted; A data transmission module is configured to transmit the target data using a target path based on the data transmission parameters and the transmission priority, wherein the target path is a preset main path or a backup path with the highest stability when the preset main path is unavailable.

11. A network status monitoring and optimization processing device, characterized in that: It comprises a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to implement the network status monitoring and optimization processing method as described in any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, the network status monitoring and optimization processing method according to any one of claims 1 to 9 is implemented.

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