Data transmission method and system based on low-delay optimization and computer readable storage medium

Abstract

The invention discloses a data transmission method and system based on low-delay optimization and a computer readable storage medium, and particularly relates to the technical field of low delay. Comprising a signal data acquisition step, a signal data division step, a signal data acquisition step, a signal data analysis step, a comprehensive analysis step, a low-delay discrimination step and a data transmission optimization step. Historical transmission signal data are obtained and divided into areas, then transmission channel states, network node processing and transmission environment interference data of all sub-data areas are collected, a low-delay transmission reasonable index is obtained through analysis and calculation, whether transmission is normal or not is judged through comparison with a preset interval, and intelligent optimization processing is carried out when transmission is abnormal. According to the method, multi-aspect data influencing the data transmission delay can be comprehensively collected, the relation of all factors can be accurately analyzed, comprehensive evaluation indexes are constructed to accurately measure the transmission performance, then targeted optimization is achieved, the data transmission delay is effectively reduced, and the requirement for low-delay data transmission in the communication field is met.

Description

Technical Field

[0001] This invention relates to the field of low-latency technology, and more specifically, to a data transmission method, system, and computer-readable storage medium optimized for low latency. Background Technology

[0002] In today's highly digitalized era, the importance of data transmission is increasingly prominent, and its applications are extremely wide-ranging. In the communications industry, whether it's everyday voice calls and video chats, or various new applications supported by the rapidly developing 5G network, all have strict requirements for the real-time performance and low latency of data transmission.

[0003] Current data transmission optimization techniques have been proposed; for example, some techniques attempt to reduce data transmission latency by optimizing network routing algorithms and selecting the optimal transmission path based on the real-time network conditions.

[0004] However, in real-world scenarios, this system still has some shortcomings, such as: incomplete data collection: traditional technologies do not comprehensively collect data on factors affecting data transmission latency during the data transmission latency optimization process. They only focus on some key factors, such as network routing or node hardware performance, while neglecting data collection on transmission channel status, network node data processing, and transmission environment interference, making it difficult to fully understand the actual data transmission environment and formulate targeted optimization strategies; imprecise analysis methods: existing data transmission latency analysis methods are not precise enough, mostly based on simple models or experience, failing to fully consider the complex relationships between various influencing factors; and a lack of a comprehensive indicator to fully evaluate the rationality of data transmission latency. Existing evaluation methods often only focus on a single factor or some factors, failing to measure whether data transmission is in a reasonable low-latency state as a whole, making it difficult to accurately evaluate the performance of the data transmission system, and hindering the timely detection of potential latency problems and the implementation of effective optimization measures. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide a data transmission method based on low latency optimization, thereby addressing the problems raised in the background art through the field of low latency technology.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a data transmission method based on low latency optimization, comprising: S1: Signal Data Acquisition: Acquire historically transmitted signal data and store it in a database; S2: Signal data partitioning: Based on the analysis of the target's historical transmission signal data, the signal data is determined as the target data region, which is then divided into various sub-data regions, and the sub-data regions are sequentially labeled i=1, 2, ..., n; S3: Signal Data Acquisition: Used to acquire transmission channel status data, network node processing data, and transmission environment interference data for each sub-data area, and transmit the acquired data to the signal data analysis step; S4: Signal Data Analysis: This step analyzes the data from the signal data acquisition step and transmits the results to the comprehensive analysis step; it includes a transmission channel analysis unit, a network node analysis unit, and a transmission environment analysis unit. S5: Comprehensive Analysis: Used to establish a comprehensive analysis model, import the data transmitted from the resource information analysis module into the comprehensive analysis model, calculate the low-latency transmission rationality index of the target data area, and transmit it to the resource verification module; includes a comprehensive analysis unit; S6: Low latency determination: Compare the preset range of the reasonable low latency transmission index with the reasonable low latency transmission index of the target data area and transmit the result to the data transmission optimization step; S7: Data transmission optimization step: Receive data from the low-latency discrimination step, optimize the data, and send it to relevant management personnel; data optimization unit.

[0007] Preferably, the transmission channel state data includes multipath fading depth, channel delay spread, and channel coherence bandwidth, denoted as Cs, Ck, and Cw, respectively; the network node processing data includes node queue overflow rate, node internal data forwarding delay, and node buffer hit rate, denoted as Wy, Wj, and Wh, respectively; and the transmission environment interference data includes radio frequency interference field strength, electromagnetic pulse interference energy, and power line harmonic distortion rate, denoted as Sg, Sd, and Sx, respectively.

[0008] Preferably, the transmission channel analysis unit is used to establish a transmission channel analysis model, import the transmission channel state data transmitted in the signal data acquisition step into the transmission channel analysis model, and calculate the transmission channel coefficient value of the target data region. The calculation method of the transmission channel analysis model is as follows: , P1 represents the transmission channel state coefficient value of the target data region, Cs i Ck represents the multipath fading depth of the i-th sub-data region. i Cw represents the channel delay spread of the i-th sub-data region. i Let represent the channel coherence bandwidth of the i-th sub-data region, e represent the natural constant, and n represent the total number of sub-data regions.

[0009] Preferably, the network node analysis unit is used to establish a network node analysis model, import the network node processing data transmitted in the signal data acquisition step into the network node analysis model, and calculate the network node state coefficient values ​​of the target data area. The calculation method of the network node analysis model is as follows: , P2 represents the network node state coefficient value of the target data region, Wy i Wj represents the node queue overflow rate of the i-th sub-data region. i Wh represents the data forwarding delay within the node of the i-th sub-data region. i Let represent the node cache hit rate of the i-th sub-data region, e represent the natural constant, and n represent the total number of sub-data regions.

[0010] Preferably, the transmission environment analysis unit is used to establish a transmission environment analysis model, import the transmission environment interference data transmitted in the signal data acquisition step into the transmission environment analysis model, and calculate the transmission environment dynamic coefficient value of the target data area. The calculation method of the transmission environment analysis model is as follows: , P3 represents the dynamic coefficient value of the transmission environment of the target data area, Sg i Sd represents the radio frequency interference field strength of the i-th sub-data region. i Sx represents the electromagnetic pulse interference energy of the i-th sub-data region. i Let e ​​represent the power line harmonic distortion rate of the i-th sub-data region, e represent the natural constant, and n represent the total number of sub-data regions.

[0011] Preferably, the comprehensive analysis unit is used to establish a comprehensive analysis model, importing the transmission channel state coefficient value, network node state coefficient value, and transmission environment dynamic coefficient value from the resource information analysis module into the comprehensive analysis model, and calculating the low-latency transmission rationality index of the target data area. The specific calculation formula is as follows: , Where η represents the low-latency transmission rationality index of the target data area, P1 represents the transmission channel state coefficient value of the target data area, P2 represents the network node state coefficient value of the target data area, and P3 represents the transmission environment dynamic coefficient value of the target data area.

[0012] Preferably, the preset range of the low-latency transmission reasonable index is [η]. cmin η lmax The data transmission allocation degree is denoted as β, and its specific acquisition method is as follows: , When η < η c or η>η l When low-latency data transmission in the target data area fails, the data transmission optimization step is initiated; when η cmin ≤η≤η lmaxThis indicates that data transmission is performed with low latency.

[0013] Preferably, the data optimization unit performs intelligent optimization when low-latency data transmission in the target data region encounters anomalies, and simultaneously generates an optimization index denoted as θ; the optimization index is compared with the data transmission allocation degree, using the following specific formula: ε represents a positive number that is infinitely close to 0.

[0014] A data transmission system optimized for low latency includes the following modules: Signal data acquisition module: Acquires historically transmitted signal data and stores it in a database; Signal data partitioning module: Based on the analysis of historical signal data transmitted by the target, the signal data is identified as the target data region, which is then divided into various sub-data regions, and the sub-data regions are sequentially labeled i=1, 2, ..., n; Signal data acquisition module: used to acquire transmission channel status data, network node processing data and transmission environment interference data of each sub-data area, and transmit the acquired data to the signal data analysis module; Signal data analysis module: used to analyze the data from the signal data acquisition module and transmit the results to the comprehensive analysis module; it includes a transmission channel analysis unit, a network node analysis unit, and a transmission environment analysis unit. Comprehensive Analysis Module: Used to establish a comprehensive analysis model, import the data transmitted from the resource information analysis module into the comprehensive analysis model, calculate the low-latency transmission rationality index of the target data area, and transmit it to the resource verification module; includes a comprehensive analysis unit; Low-latency discrimination module: compares the preset range of the low-latency transmission reasonable index with the low-latency transmission reasonable index of the target data area and transmits the result to the data transmission optimization module; Data transmission optimization module: Receives data from the low-latency discrimination module, optimizes the data, and sends it to relevant management personnel; data optimization unit.

[0015] Preferably, a computer program is stored that can be loaded by a processor and executed according to any one of the methods of claims 1-8.

[0016] The technical effects and advantages of this invention are as follows: 1. This invention comprehensively collects transmission channel status data, network node processing data, and transmission environment interference data for each sub-data area through signal data acquisition steps. Detailed acquisition of transmission channel status data, such as multipath fading depth, channel delay spread, and channel coherence bandwidth, helps to accurately understand the channel's transmission characteristics and predict signal transmission quality in advance. Acquiring network node processing data, such as node queue overflow rate, internal data forwarding delay, and node buffer hit rate, allows for in-depth analysis of network node operating status and timely identification of node performance bottlenecks. Acquiring transmission environment interference data, such as radio frequency interference field strength, electromagnetic pulse interference energy, and power line harmonic distortion rate, provides a comprehensive understanding of the transmission environment's interference situation, offering accurate data for subsequent optimization and thus precisely grasping the actual data transmission environment, providing strong support for optimizing transmission strategies.

[0017] 2. This invention utilizes a transmission channel analysis unit, a network node analysis unit, and a transmission environment analysis unit to establish corresponding analysis models. These models can deeply analyze the complex relationships between various factors and accurately calculate the transmission channel coefficient value, network node state coefficient value, and transmission environment dynamic coefficient value of the target data area. Through these precise analysis results, the cause of data transmission delay can be accurately determined—whether it is a problem with the transmission channel, a performance bottleneck of the network node, or interference from the transmission environment—providing a scientific basis for formulating targeted optimization strategies and improving the accuracy and effectiveness of optimization measures. 3. This invention establishes a comprehensive analysis model through a comprehensive analysis unit, importing transmission channel state coefficients, network node state coefficients, and transmission environment dynamic coefficients into the model to calculate a low-latency transmission rationality index for the target data area. This comprehensive evaluation index can measure the rationality of data transmission as a whole, fully reflecting whether data transmission is in a reasonable low-latency state. By comparing with a preset interval, potential latency problems can be identified in a timely manner, accurately evaluating the performance of the data transmission system and providing a clear direction for the implementation of optimization measures. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the method structure of the present invention.

[0019] Figure 2 This is a schematic diagram of the system structure of the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] As attached Figure 1 The diagram shows a data transmission method based on low-latency optimization, comprising S1-S7: S1: Signal Data Acquisition: Acquire historically transmitted signal data and store it in a database; S2: Signal data partitioning: Based on the analysis of the target's historical transmission signal data, the signal data is determined as the target data region, which is then divided into various sub-data regions, and the sub-data regions are sequentially labeled i=1, 2, ..., n; S3: Signal Data Acquisition: Used to acquire transmission channel status data, network node processing data, and transmission environment interference data for each sub-data area, and transmit the acquired data to the signal data analysis step.

[0022] In this embodiment, it should be specifically noted that the transmission channel state data includes multipath fading depth, channel delay spread, and channel coherence bandwidth, denoted as Cs, Ck, and Cw, respectively; the network node processing data includes node queue overflow rate, node internal data forwarding delay, and node buffer hit rate, denoted as Wy, Wj, and Wh, respectively; and the transmission environment interference data includes radio frequency interference field strength, electromagnetic pulse interference energy, and power line harmonic distortion rate, denoted as Sg, Sd, and Sx, respectively.

[0023] Further, the multipath fading depth acquisition process involves: A signal generator typically sends a known test signal to the channel, and a spectrum analyzer or vector signal analyzer receives the signal at the receiver. By comparing the strengths of the transmitted and received signals, the amplitude of signal strength changes at different times is calculated to determine the multipath fading depth. The channel delay spread acquisition process involves sending pulse signals with precise time stamps, and at the receiver, correlation detection technology is used to measure the time difference of arrival of signals from different paths. Wideband signals can be used, as their wider spectrum allows for better differentiation of delays along different paths. By measuring multiple pulse signals, the distribution of delays is statistically analyzed, thus obtaining the channel delay spread data. The channel coherence bandwidth involves sending multiple sinusoidal or swept-frequency signals at different frequencies, and at the receiver, the amplitude and phase changes of each frequency signal are measured. By analyzing the correlation between different frequency signals, when the correlation is below a certain threshold, the corresponding frequency interval is the channel coherence bandwidth. Alternatively, a channel sounder can be used, which can directly measure the channel's frequency response to determine the channel coherence bandwidth. Finally, the node queue overflow rate is determined by setting a counter in the queue management module of the network node to count the number of queue overflows. Simultaneously, the number of data packets arriving and processed per unit time is recorded. The node queue overflow rate equals the number of queue overflows divided by the total number of data packets arriving. By continuously monitoring these data over a period of time, the node queue overflow rate can be calculated. Internal node data forwarding latency: In the data packet processing flow within the node, timestamps are set at the points where data packets enter and leave the forwarding queue. The forwarding latency of the data packets within the node is obtained by calculating the difference between these two timestamps. Node cache hit rate: The number of cache hits and the total number of data requests are recorded. The node cache hit rate equals the number of cache hits divided by the total number of data requests. Counters and log recording functions can be set in the cache to record each data request and cache hit, and the cache hit rate can be periodically calculated. Radio frequency interference field strength: The antenna of the field strength meter is placed at the location to be measured, and the frequency range and measurement parameters of the field strength meter are adjusted to accurately measure the field strength of the interference signal. Electromagnetic pulse interference energy: An electromagnetic pulse measuring instrument is used to collect electromagnetic pulse interference energy. This measuring instrument typically has a highly sensitive sensor capable of detecting changes in the electric and magnetic field strength of electromagnetic pulses. During measurement, the measuring instrument is placed in an area potentially susceptible to electromagnetic pulse interference, and the energy value of each electromagnetic pulse event is recorded. Power line harmonic distortion rate: A power quality analyzer is connected to the power line to measure the voltage and current signals. By performing Fourier transforms on these signals, the harmonic components are analyzed, and the harmonic distortion rate is calculated. Measurements can be performed at different power line nodes to monitor the distribution of power line harmonic distortion rate.

[0024] S4: Signal Data Analysis: This step analyzes the data from the signal data acquisition step and transmits the results to the comprehensive analysis step. It includes a transmission channel analysis unit, a network node analysis unit, and a transmission environment analysis unit.

[0025] In this embodiment, it should be specifically noted that the transmission channel analysis unit is used to establish a transmission channel analysis model, import the transmission channel state data transmitted in the signal data acquisition step into the transmission channel analysis model, and calculate the transmission channel coefficient value of the target data region. The calculation method of the transmission channel analysis model is as follows: , P1 represents the transmission channel state coefficient value of the target data region, Cs i Ck represents the multipath fading depth of the i-th sub-data region. i Cw represents the channel delay spread of the i-th sub-data region. i Let represent the channel coherence bandwidth of the i-th sub-data region, e represent the natural constant, and n represent the total number of sub-data regions.

[0026] In this embodiment, it should be specifically noted that the network node analysis unit is used to establish a network node analysis model. The network node processing data transmitted during the signal data acquisition step is imported into the network node analysis model to calculate the network node state coefficient values ​​for the target data region. The calculation method of the network node analysis model is as follows: , P2 represents the network node state coefficient value of the target data region, Wy i Wj represents the node queue overflow rate of the i-th sub-data region. i Wh represents the data forwarding delay within the node of the i-th sub-data region. i Let represent the node cache hit rate of the i-th sub-data region, e represent the natural constant, and n represent the total number of sub-data regions.

[0027] In this embodiment, it should be specifically noted that the transmission environment analysis unit is used to establish a transmission environment analysis model. The transmission environment interference data transmitted during the signal data acquisition step is imported into the transmission environment analysis model to calculate the dynamic coefficient value of the transmission environment in the target data area. The calculation method of the transmission environment analysis model is as follows: , P3 represents the dynamic coefficient value of the transmission environment of the target data area, Sg i Sd represents the radio frequency interference field strength of the i-th sub-data region. i Sx represents the electromagnetic pulse interference energy of the i-th sub-data region. iLet e ​​represent the power line harmonic distortion rate of the i-th sub-data region, e represent the natural constant, and n represent the total number of sub-data regions.

[0028] S5: Comprehensive Analysis: Used to establish a comprehensive analysis model, import the data transmitted from the signal data analysis step into the comprehensive analysis model, calculate the reasonable index of low-latency transmission in the target data area, and transmit it to the comprehensive judgment step; includes a comprehensive analysis unit.

[0029] In this embodiment, it should be specifically noted that the comprehensive analysis unit is used to establish a comprehensive analysis model. The transmission channel state coefficient value, network node state coefficient value, and transmission environment dynamic coefficient value from the resource information analysis module are imported into the comprehensive analysis model to calculate the low-latency transmission rationality index for the target data area. The specific calculation formula is as follows: , Where η represents the low-latency transmission rationality index of the target data area, P1 represents the transmission channel state coefficient value of the target data area, P2 represents the network node state coefficient value of the target data area, and P3 represents the transmission environment dynamic coefficient value of the target data area.

[0030] S6: Low latency judgment: Compare the preset range of the low latency transmission reasonable index with the low latency transmission reasonable index of the target data area and transmit the result to the data transmission optimization step.

[0031] In this embodiment, it should be specifically noted that the preset range [η] of the low-latency transmission reasonable index is... cmin η lmax The data transmission allocation degree is denoted as β, and its specific acquisition method is as follows: , When η < η c or η>η l When low-latency data transmission in the target data area fails, the data transmission optimization step is initiated; when η cmin ≤η≤η lmax This indicates that data transmission is performed with low latency.

[0032] S7: Data transmission optimization step: Receive data from the low-latency discrimination step, optimize the data, and send it to relevant management personnel; data optimization unit.

[0033] In this embodiment, it should be specifically noted that the data optimization unit performs intelligent optimization processing when low-latency data transmission in the target data area encounters anomalies, and simultaneously generates an optimization index denoted as θ; the optimization index is compared with the data transmission allocation degree, and the specific formula is as follows: ε represents a positive number that is infinitely close to 0.

[0034] As attached Figure 2 As shown, a data transmission system based on low latency optimization includes the following modules: Signal data acquisition module: Acquires historically transmitted signal data and stores it in a database; Signal data partitioning module: Based on the analysis of historical signal data transmitted by the target, the signal data is identified as the target data region, which is then divided into various sub-data regions, and the sub-data regions are sequentially labeled i=1, 2, ..., n; Signal data acquisition module: used to acquire transmission channel status data, network node processing data and transmission environment interference data of each sub-data area, and transmit the acquired data to the signal data analysis module; Signal data analysis module: used to analyze the data from the signal data acquisition module and transmit the results to the comprehensive analysis module; it includes a transmission channel analysis unit, a network node analysis unit, and a transmission environment analysis unit. Comprehensive Analysis Module: Used to establish a comprehensive analysis model, import the data transmitted from the resource information analysis module into the comprehensive analysis model, calculate the low-latency transmission rationality index of the target data area, and transmit it to the resource verification module; includes a comprehensive analysis unit; Low-latency discrimination module: compares the preset range of the low-latency transmission reasonable index with the low-latency transmission reasonable index of the target data area and transmits the result to the data transmission optimization module; Data transmission optimization module: Receives data from the low-latency discrimination module, optimizes the data, and sends it to relevant management personnel; data optimization unit.

[0035] This application also discloses a computer-readable storage medium that stores a data transmission computer-readable storage medium that can be loaded and executed by a processor as described above based on low latency optimization. The computer-readable storage medium includes, for example, 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.

[0036] This invention comprehensively collects transmission channel status data, network node processing data, and transmission environment interference data for each sub-data region through signal data acquisition steps. Detailed acquisition of transmission channel status data, such as multipath fading depth, channel delay spread, and channel coherence bandwidth, helps to accurately understand the channel's transmission characteristics and predict signal transmission quality in advance. Acquiring network node processing data, such as node queue overflow rate, internal data forwarding delay, and node buffer hit rate, allows for in-depth analysis of network node operating status and timely identification of node performance bottlenecks. Acquiring transmission environment interference data, such as radio frequency interference field strength, electromagnetic pulse interference energy, and power line harmonic distortion rate, provides a comprehensive understanding of the transmission environment's interference situation, offering accurate data for subsequent optimization and precise control over the actual data transmission environment, thus providing strong support for optimizing transmission strategies. Corresponding analysis models are established using transmission channel analysis units, network node analysis units, and transmission environment analysis units. These models can deeply analyze the complex relationships between various factors and accurately calculate the transmission channel coefficient values, network node status coefficient values, and transmission environment dynamic coefficient values ​​for the target data region. These precise analytical results allow for accurate identification of the causes of data transmission delays—whether it's a problem with the transmission channel, a performance bottleneck in the network nodes, or interference from the transmission environment. This provides a scientific basis for developing targeted optimization strategies, improving the accuracy and effectiveness of optimization measures. A comprehensive analysis model is established using a comprehensive analysis unit, importing transmission channel state coefficients, network node state coefficients, and dynamic coefficients of the transmission environment into the model to calculate a low-latency transmission rationality index for the target data area. This comprehensive evaluation index measures the rationality of data transmission as a whole, fully reflecting whether data transmission is in a reasonable low-latency state. By comparing with a preset interval, potential delay problems can be identified in a timely manner, accurately assessing the performance of the data transmission system and providing a clear direction for implementing optimization measures.

[0037] Secondly, the accompanying drawings of the embodiments disclosed in this invention only involve the structures involved in the embodiments disclosed in this invention. Other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of this invention can be combined with each other. The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A data transmission method based on low-latency optimization, characterized in that, include: S1: Signal Data Acquisition: Acquire historically transmitted signal data and store it in a database; S2: Signal data partitioning: Based on the analysis of the target's historical transmission signal data, the signal data is determined as the target data region, which is then divided into various sub-data regions, and the sub-data regions are sequentially labeled i=1, 2, ..., n; S3: Signal Data Acquisition: Used to acquire transmission channel status data, network node processing data, and transmission environment interference data for each sub-data area, and transmit the acquired data to the signal data analysis step; S4: Signal Data Analysis: Used to analyze the data from the signal data acquisition step and transmit the results to the comprehensive analysis step; It includes a transmission channel analysis unit, a network node analysis unit, and a transmission environment analysis unit; S5: Comprehensive Analysis: Used to establish a comprehensive analysis model, import the data transmitted by the resource information analysis module into the comprehensive analysis model, calculate the low-latency transmission reasonable index of the target data area, and transmit it to the resource verification module; Includes a comprehensive analysis unit; S6: Low latency determination: Compare the preset range of the reasonable low latency transmission index with the reasonable low latency transmission index of the target data area and transmit the result to the data transmission optimization step; S7: Data transmission optimization: Receives data from the low-latency discrimination step, optimizes the data, and sends it to relevant management personnel; data optimization unit.

2. The data transmission method based on low-latency optimization according to claim 1, characterized in that: The transmission channel state data includes multipath fading depth, channel delay spread, and channel coherence bandwidth, denoted as Cs, Ck, and Cw, respectively; the network node processing data includes node queue overflow rate, node internal data forwarding delay, and node buffer hit rate, denoted as Wy, Wj, and Wh, respectively; the transmission environment interference data includes radio frequency interference field strength, electromagnetic pulse interference energy, and power line harmonic distortion rate, denoted as Sg, Sd, and Sx, respectively.

3. The data transmission method based on low-latency optimization according to claim 1, characterized in that: The transmission channel analysis unit is used to establish a transmission channel analysis model. It imports the transmission channel state data transmitted during the signal data acquisition step into the transmission channel analysis model and calculates the transmission channel coefficient values ​​for the target data region. The calculation method of the transmission channel analysis model is as follows: ， P1 represents the transmission channel state coefficient value of the target data region, Cs i Ck represents the multipath fading depth of the i-th sub-data region. i Cw represents the channel delay spread of the i-th sub-data region. i Let represent the channel coherence bandwidth of the i-th sub-data region, e represent the natural constant, and n represent the total number of sub-data regions.

4. The data transmission method based on low-latency optimization according to claim 1, characterized in that: The network node analysis unit is used to establish a network node analysis model. It imports the network node processing data transmitted during the signal data acquisition step into the network node analysis model and calculates the network node state coefficient values ​​for the target data region. The calculation method of the network node analysis model is as follows: ， P2 represents the network node state coefficient value of the target data region, Wy i Wj represents the node queue overflow rate of the i-th sub-data region. i Wh represents the data forwarding delay within the node of the i-th sub-data region. i Let represent the node cache hit rate of the i-th sub-data region, e represent the natural constant, and n represent the total number of sub-data regions.

5. The data transmission method based on low-latency optimization according to claim 1, characterized in that: The transmission environment analysis unit is used to establish a transmission environment analysis model. It imports the transmission environment interference data transmitted during the signal data acquisition step into the transmission environment analysis model and calculates the dynamic coefficient value of the transmission environment for the target data area. The calculation method of the transmission environment analysis model is as follows: ， P3 represents the dynamic coefficient value of the transmission environment of the target data area, Sg i Sd represents the radio frequency interference field strength of the i-th sub-data region. i Sx represents the electromagnetic pulse interference energy of the i-th sub-data region. i Let e ​​represent the power line harmonic distortion rate of the i-th sub-data region, e represent the natural constant, and n represent the total number of sub-data regions.

6. The data transmission method based on low-latency optimization according to claim 1, characterized in that: The comprehensive analysis unit is used to establish a comprehensive analysis model. It imports the transmission channel state coefficient values, network node state coefficient values, and transmission environment dynamic coefficient values ​​from the resource information analysis module into the comprehensive analysis model to calculate the low-latency transmission rationality index for the target data area. The specific calculation formula is as follows: ， Where η represents the low-latency transmission rationality index of the target data area, P1 represents the transmission channel state coefficient value of the target data area, P2 represents the network node state coefficient value of the target data area, and P3 represents the transmission environment dynamic coefficient value of the target data area.

7. The data transmission method based on low-latency optimization according to claim 1, characterized in that: The preset range of the low-latency transmission reasonable index [η] cmin η lmax The data transmission allocation degree is denoted as β, and its specific acquisition method is as follows: ， When η < η c or η>η l When low-latency data transmission in the target data area fails, the data transmission optimization step is initiated; when η cmin ≤η≤η lmax This indicates that data transmission is performed with low latency.

8. The data transmission method based on low-latency optimization according to claim 1, characterized in that: The data optimization unit is used to intelligently optimize data transmission in the target data region when low-latency data transmission becomes abnormal, and generates an optimization index denoted as θ. The optimization index is compared with the data transmission allocation degree, as shown in the following formula: ε represents a positive number that is infinitely close to 0.

9. A data transmission method based on low-latency optimization according to claim 1, characterized in that: A data transmission system optimized for low latency, specifically comprising: Signal data acquisition module: Acquires historically transmitted signal data and stores it in a database; Signal data partitioning module: Based on the analysis of historical signal data transmitted by the target, the signal data is identified as the target data region, which is then divided into various sub-data regions, and the sub-data regions are sequentially labeled i=1, 2, ..., n; Signal data acquisition module: used to acquire transmission channel status data, network node processing data and transmission environment interference data of each sub-data area, and transmit the acquired data to the signal data analysis module; Signal data analysis module: used to analyze the data from the signal data acquisition module and transmit the results to the comprehensive analysis module; it includes a transmission channel analysis unit, a network node analysis unit, and a transmission environment analysis unit. Comprehensive Analysis Module: Used to establish a comprehensive analysis model, import the data transmitted from the resource information analysis module into the comprehensive analysis model, calculate the low-latency transmission rationality index of the target data area, and transmit it to the resource verification module; includes a comprehensive analysis unit; Low-latency discrimination module: compares the preset range of the low-latency transmission reasonable index with the low-latency transmission reasonable index of the target data area and transmits the result to the data transmission optimization module; Data transmission optimization module: Receives data from the low-latency discrimination module, optimizes the data, and sends it to relevant management personnel; data optimization unit.

10. A computer-readable storage medium for data transmission optimized for low latency, characterized in that, The computer program is stored that can be loaded by a processor and executed according to any one of the methods described in claims 1-8.

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