Adaptive real-time simulation data transmission method and device based on pre-negotiation

Abstract

An embodiment of the present application provides an adaptive real-time simulation data transmission method and device based on pre-negotiation, the method comprising: a data sending end sends data to a data receiving end according to an initial data transmission unit value and a preset time interval to perform a communication test, and obtain corresponding test data; the data receiving end calculates the communication throughput, communication packet loss rate, communication transmission efficiency, communication delay and communication processing capability according to the test data, and constructs a total index model and a comprehensive performance index model; the total index formula is calculated according to the entropy weight method, the test data is substituted into the total index formula to obtain the total index value, the comprehensive performance index model is fitted with a least squares algorithm according to the total index value, the comprehensive performance formula is determined, the optimal comprehensive performance index is obtained according to the gradient ascent method, and the data sending end performs data transmission according to the optimal comprehensive performance index. The present application can improve the efficiency and reliability of simulation data transmission based on pre-negotiation parameters.

Description

Technical Field

[0001] The present application relates to the field of data processing, and in particular to a method and device for adaptive real-time simulation data transmission based on pre-negotiation. Background Art

[0002] With the continuous development of simulation technology, especially in the field of real-time simulation systems, efficient and reliable communication mechanisms have become the key to ensure the stable operation of the system. Traditional communication protocols mainly refer to protocols based on the TCP / IP model, which is a set of rules and standards for data exchange in the network. Although the TCP / IP model protocol is very effective in many application scenarios, in the field of real-time simulation communication, it is often difficult to balance transmission efficiency, reliability and flexibility when facing complex and changing network environments and diverse terminal devices.

[0003] Point-to-point communication refers to the receiving end notifying the sending end of the maximum data packet number that has been successfully received through a response signal. As a basic communication method, it is widely used in real-time simulation systems.

[0004] However, during the data transmission process of traditional point-to-point communication, when the network conditions are unstable or the processing power of the terminal device is limited, the traditional protocol may not be able to adjust the transmission parameters in time, and there are challenges in data reliability and effective use of bandwidth. In addition, it lacks sufficient flexibility and adaptability, and it is difficult to meet the real-time simulation system's requirements for efficient and reliable communication. Summary of the invention

[0005] In view of the problems in the prior art, the present application provides a method and device for adaptive real-time simulated data transmission based on pre-negotiation, which can improve the efficiency and reliability of simulated data transmission based on pre-negotiation parameters.

[0006] In order to solve at least one of the above problems, the present application provides the following technical solutions:

[0007] In a first aspect, the present application provides an adaptive real-time simulation data transmission method based on pre-negotiation, comprising:

[0008] Determine an initial maximum transmission unit value of the corresponding transmission data packet according to the size of the buffer area, and send the initial maximum transmission unit value to the data sending end, so that the data sending end performs a communication test operation with the data receiving end according to the initial maximum transmission unit value and a preset initial time interval after receiving the initial maximum transmission unit value, and determines corresponding test data;

[0009] Determine the corresponding communication throughput, communication packet loss rate, communication transmission efficiency, communication delay and communication processing capacity according to the test data, perform an abstract model construction operation according to the communication throughput and the communication packet loss rate, determine the corresponding total index model, perform an abstract model construction operation according to the communication transmission efficiency, the communication delay and the communication processing capacity, and determine the corresponding comprehensive performance index model, wherein the comprehensive performance index model and the total index model are both used to reflect communication performance;

[0010] A weight calculation operation is performed on the total index model according to a preset entropy weight method and the test data obtained after the communication test to obtain the corresponding weights of each index in the total index model; a corresponding total index formula is determined according to the weights of each index; a fitting operation is performed on the comprehensive performance index model according to the test data, the total index formula and a preset least squares algorithm to determine the corresponding comprehensive performance formula; an iterative operation is performed on the comprehensive performance formula according to a preset gradient ascent algorithm to determine the corresponding optimal comprehensive performance index; a corresponding optimal transmission unit value and an optimal time interval are determined according to the optimal comprehensive performance index; and the optimal transmission unit value and the optimal time interval are sent to the data sending end so that the data sending end transmits data according to the optimal transmission unit value and the optimal time interval.

[0011] Further, the determining of the corresponding initial maximum transmission unit value according to the buffer size includes:

[0012] Performing a buffer value calculation operation on the receiving end to determine a corresponding maximum value of the receiving end buffer;

[0013] A multiple value operation is performed based on half of the maximum value of the receiving end buffer area to determine the corresponding initial maximum transmission unit value, wherein the multiple value operation is to take the largest multiple of a preset integer within the range of half of the maximum value of the receiving end buffer area.

[0014] Further, the sending of the initial maximum transmission unit value to the data transmitting end so that the data transmitting end performs a communication test operation with the data receiving end according to the initial maximum transmission unit value and a preset initial time interval after receiving the initial maximum transmission unit value, and determines the corresponding test data, including:

[0015] The initial maximum transmission unit value is sent to the data transmitting end, so that after receiving the initial maximum transmission unit value, the data transmitting end gradually decreases the initial maximum transmission unit value according to the preset integer to determine a plurality of corresponding maximum transmission unit values, gradually increases the preset initial time interval according to a preset frame interval increment to determine a plurality of corresponding time intervals, and performs sample combination operations on the plurality of maximum transmission unit values ​​and the plurality of time intervals to determine a plurality of sample groups;

[0016] A communication test operation is performed with the data receiving end according to the multiple sample groups and the preset number of communications, and test data corresponding to each sample group is determined, wherein the test data includes the total amount of data to be transmitted, the number of received data packets, the maximum transmission unit, the sum of the Ethernet protocol overhead outside the application layer, the size of the application layer data packet header, the transmission time of each Ethernet frame, the processing time of each Ethernet frame, the network bandwidth and the minimum time interval.

[0017] Furthermore, before determining the corresponding communication throughput, communication packet loss rate, communication transmission efficiency, communication delay and communication processing capability according to the test data, it includes:

[0018] A model building operation is performed according to a preset total amount of data to be transmitted, a preset maximum transmission unit, a preset sum of Ethernet protocol overhead outside the application layer, and a preset application layer data packet header size to determine a corresponding communication transmission efficiency model;

[0019] Perform a model building operation according to a preset total amount of data to be transmitted, a preset maximum transmission unit, a preset transmission time of each Ethernet frame, a preset processing time of each Ethernet frame, and a preset minimum time interval to determine a corresponding communication delay model;

[0020] A model building operation is performed according to the preset processing time of each Ethernet frame and the preset minimum time interval to determine the corresponding communication processing capability model.

[0021] Further, the determining of the corresponding communication throughput, communication packet loss rate, communication transmission efficiency, communication delay and communication processing capability according to the test data includes:

[0022] Determine the corresponding communication throughput according to the test data and a preset communication throughput formula;

[0023] Determine the corresponding communication packet loss rate according to the test data and a preset communication packet loss rate formula;

[0024] Determining corresponding communication transmission efficiency according to the test data and the communication transmission efficiency model;

[0025] Determining corresponding communication delay according to the test data and the communication delay model;

[0026] The corresponding communication processing capability is determined according to the test data and the communication processing capability model.

[0027] Further, the total index model is weighted according to the preset entropy weight method and the test data obtained after the communication test to obtain the corresponding weight of each indicator in the total index model, and the corresponding total index formula is determined according to the weight of each indicator, including:

[0028] Performing an information entropy calculation operation on the communication throughput and the communication packet loss rate obtained after the communication test to determine corresponding communication throughput information entropy and communication packet loss rate information entropy;

[0029] Determine the corresponding communication throughput weight and communication packet loss rate weight according to the communication throughput information entropy and the communication packet loss rate information entropy;

[0030] The communication throughput weight and the communication packet loss rate weight are substituted into the total indicator model to determine a corresponding total indicator formula.

[0031] Furthermore, the fitting operation is performed on the comprehensive performance index model according to the test data, the total index formula and a preset least squares algorithm to determine the corresponding comprehensive performance formula, including:

[0032] Substituting the communication throughput and the communication packet loss rate obtained according to the test data into the total index formula to determine the corresponding total index value, assigning the total index value to the comprehensive performance index model to determine the corresponding comprehensive performance index value;

[0033] Performing a target vector construction operation according to the comprehensive performance index value to determine a corresponding target vector, wherein the comprehensive performance index value corresponds to the test data;

[0034] Performing a matrix construction operation on the communication transmission efficiency, the communication delay, and the communication processing capability obtained according to the test data to determine a corresponding data matrix;

[0035] A fitting operation is performed according to a preset least squares algorithm, the data matrix and the target vector to determine the weight of each indicator in the corresponding comprehensive performance indicator model, and the comprehensive performance indicator model is substituted according to the weight of each indicator in the comprehensive performance indicator model to determine the corresponding comprehensive performance formula.

[0036] In a second aspect, the present application provides an adaptive real-time simulation data transmission device based on pre-negotiation, comprising:

[0037] A communication test module, used to determine an initial maximum transmission unit value of a corresponding transmission data packet according to a buffer size, and send the initial maximum transmission unit value to the data transmitting end, so that the data transmitting end performs a communication test operation with the data receiving end according to the initial maximum transmission unit value and a preset initial time interval after receiving the initial maximum transmission unit value, and determines corresponding test data;

[0038] An indicator model determination module is used to determine the corresponding communication throughput, communication packet loss rate, communication transmission efficiency, communication delay and communication processing capacity according to the test data, perform an abstract model construction operation according to the communication throughput and the communication packet loss rate, and determine the corresponding total indicator model, perform an abstract model construction operation according to the communication transmission efficiency, the communication delay and the communication processing capacity, and determine the corresponding comprehensive performance indicator model, wherein the comprehensive performance indicator model and the total indicator model are both used to reflect communication performance;

[0039] The optimal comprehensive performance index determination module is used to perform a weight calculation operation on the total index model according to a preset entropy weight method and the test data obtained after the communication test, obtain the corresponding weight of each indicator in the total index model, determine the corresponding total index formula according to the weight of each indicator, perform a fitting operation on the comprehensive performance index model according to the test data, the total index formula and a preset least squares algorithm, determine the corresponding comprehensive performance formula, iterate the comprehensive performance formula according to a preset gradient ascent algorithm, determine the corresponding optimal comprehensive performance index, determine the corresponding optimal transmission unit value and the optimal time interval according to the optimal comprehensive performance index, and send the optimal transmission unit value and the optimal time interval to the data sending end, so that the data sending end performs data transmission according to the optimal transmission unit value and the optimal time interval.

[0040] In a third aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the pre-negotiation-based adaptive real-time simulation data transmission method when executing the program.

[0041] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the pre-negotiation-based adaptive real-time simulation data transmission method.

[0042] In a fifth aspect, the present application provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of the pre-negotiation-based adaptive real-time simulation data transmission method.

[0043] It can be seen from the above technical scheme that the present application provides an adaptive real-time simulation data transmission method and device based on pre-negotiation, wherein the data sending end sends data to the data receiving end according to the initial data transmission unit value and the preset time interval for communication testing to obtain corresponding test data; the data receiving end calculates the communication throughput, communication packet loss rate, communication transmission efficiency, communication delay and communication processing capability according to the test data, and constructs a total index model and a comprehensive performance index model; the total index formula is calculated according to the entropy weight method, the test data is substituted into the total index formula to obtain the total index value, the comprehensive performance index model is fitted with the least squares algorithm according to the total index value, the comprehensive performance formula is determined, the optimal comprehensive performance index is obtained according to the gradient ascent method, and the data sending end performs data transmission according to the optimal comprehensive performance index, thereby improving the efficiency and reliability of simulation data transmission based on pre-negotiation parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0045] Figure 1 This is one of the flow charts of the method for adaptive real-time simulation data transmission based on pre-negotiation in an embodiment of the present application;

[0046] Figure 2 This is a second flow chart of the method for adaptive real-time simulation data transmission based on pre-negotiation in an embodiment of the present application;

[0047] Figure 3 The third flowchart of the method for adaptive real-time simulation data transmission based on pre-negotiation in the embodiment of the present application;

[0048] Figure 4 This is a fourth flow chart of the method for adaptive real-time simulation data transmission based on pre-negotiation in an embodiment of the present application;

[0049] Figure 5 This is a fifth flow chart of the method for adaptive real-time simulation data transmission based on pre-negotiation in an embodiment of the present application;

[0050] Figure 6 This is a sixth flow chart of the method for adaptive real-time simulation data transmission based on pre-negotiation in an embodiment of the present application;

[0051] Figure 7FIG7 is a flowchart of a method for transmitting adaptive real-time simulated data based on pre-negotiation in an embodiment of the present application;

[0052] Figure 8 It is a structural diagram of a pre-negotiation-based adaptive real-time simulation data transmission device in an embodiment of the present application;

[0053] Fig. 9 It is a schematic diagram of the structure of an electronic device in an embodiment of the present application.

[0054] Reference numerals:

[0055] Electronic device 9600, central processing unit 9100, memory 9140, communication module 9110, input unit 9120, audio processor 9130, display 9160, power supply 9170, buffer memory 9141, application / function storage unit 9142, data storage unit 9143, driver program storage unit 9144, antenna 9111, speaker 9131, microphone 9132. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0057] The acquisition, storage, use, and processing of data in the technical solution of this application comply with the relevant provisions of national laws and regulations.

[0058] Considering the problem that in the process of data transmission in traditional point-to-point communication, when the processing capacity of the terminal equipment is limited, the traditional protocol may not be able to adjust the transmission parameters in time, and lacks sufficient flexibility and adaptability. The present application provides a method and device for adaptive real-time simulation data transmission based on pre-negotiation, wherein the data sending end sends data to the data receiving end according to the initial data transmission unit value and the preset time interval to perform communication testing, and obtain corresponding test data; the data receiving end calculates the communication throughput, communication packet loss rate, communication transmission efficiency, communication delay and communication processing capacity according to the test data, and constructs a total index model and a comprehensive performance index model; the total index formula is calculated according to the entropy weight method, the test data is brought into the total index formula to obtain the total index value, the comprehensive performance index model is fitted with the least squares algorithm according to the total index value, the comprehensive performance formula is determined, the optimal comprehensive performance index is obtained according to the gradient ascent method, and the data sending end performs data transmission according to the optimal comprehensive performance index, thereby improving the efficiency and reliability of simulated data transmission based on pre-negotiation parameters.

[0059] In order to improve the efficiency and reliability of simulated data transmission based on pre-negotiation parameters, the present application provides an embodiment of an adaptive real-time simulated data transmission method based on pre-negotiation, see Figure 1 The pre-negotiation-based adaptive real-time simulation data transmission method specifically includes the following contents:

[0060] Step S101: determining an initial maximum transmission unit value of a corresponding transmission data packet according to the size of the buffer area, and sending the initial maximum transmission unit value to the data transmitting end, so that after receiving the initial maximum transmission unit value, the data transmitting end performs a communication test operation with the data receiving end according to the initial maximum transmission unit value and a preset initial time interval, and determines corresponding test data;

[0061] Optionally, in this embodiment, the purpose of this step is for the sending end to perform a data transmission test on the receiving end based on the initial transmission parameters obtained from the receiving end, so as to obtain corresponding test data, so as to obtain the optimal transmission parameters after the subsequent receiving end obtains the test data and processes it through an algorithm, thereby laying the foundation for flexible and adaptable data transmission.

[0062] Optionally, in this embodiment, the initial maximum transmission unit value of the corresponding transmission data packet is determined according to the buffer size.

[0063] Specifically, the maximum transmission unit (MTU) of the transmission data packet determines the maximum size of a single data packet. The initial test value of the maximum transmission unit of the transmission data packet is the maximum multiple of 128 bytes contained in half of the maximum value of the receiving end buffer. 128 bytes is a common DMA transmission block size, which can optimize DMA transmission, reduce the number of transmissions, improve transmission efficiency, and reduce the CPU burden.

[0064] Optionally, the size of the receiving end buffer area should be set to avoid wasting the receiving end buffer area and maximize the use of the buffer area. Preferably, the size of the receiving end buffer area is 4096 bytes to ensure that the receiving end B can cache at least two data packets. The initial value of the application layer maximum transmission unit MTU is calculated by the receiving end B at the beginning to calculate the maximum multiple of 128 bytes contained in half of the maximum value of the receiving end buffer area, and send it to the sending end A, which performs subsequent tests based on this, wherein the sending end A is the simulation device end.

[0065] For example, taking the buffer area of ​​the receiving end B as 4096 bytes, the initial maximum transmission unit value is 2048.

[0066] Optionally, in this embodiment, the initial maximum transmission unit value is sent to the data sending end, so that after the data sending end receives the initial maximum transmission unit value, it performs a communication test operation with the data receiving end according to the initial maximum transmission unit value and a preset initial time interval to determine the corresponding test data;

[0067] Optionally, after determining the initial maximum transmission unit value, the transmitting end A starts the communication test. Specifically, the transmitting end A determines multiple MTU samples based on the initial maximum transmission unit value, with a step size of 128 bytes, and the MTU gradually decreases to a minimum of 128 bytes. After determining the MTU sample, a corresponding time interval group is specified for each MTU sample. Preferably, the time interval group gradually increases in the range of 12 bytes to 20 bytes. It can be understood that the Ethernet standard IEEE802.3 specifies a minimum frame interval of 12 bytes (96 bit time) to ensure that the network device has enough time to process the previous frame and is ready to receive the next frame. Modern network devices take this standard into consideration when designing, and their processing time and buffer management are optimized. Preferably, they can operate efficiently within the range of 12 bytes to 20 bytes. Actual tests show that the frame interval within this range has a significant impact on network throughput and delay. A smaller frame interval can improve throughput, but a too small frame interval will increase the probability of conflict; a larger frame interval will increase delay, but can reduce device processing pressure and packet loss rate. As a relatively large value, 20 bytes can provide enough data points to evaluate the impact of different frame intervals on network performance while avoiding resource waste caused by excessive frame intervals. Therefore, it is scientific and reasonable to choose a range of 12 bytes to 20 bytes for testing.

[0068] Optionally, each MTU sample (M) and the corresponding time interval (g) are combined into a sample group (M, g). Preferably, each group (M, g) is tested 2 times. 16 times to obtain test data.

[0069] Step S102: determining the corresponding communication throughput, communication packet loss rate, communication transmission efficiency, communication delay and communication processing capability according to the test data, performing an abstract model construction operation according to the communication throughput and the communication packet loss rate, determining the corresponding total index model, performing an abstract model construction operation according to the communication transmission efficiency, the communication delay and the communication processing capability, and determining the corresponding comprehensive performance index model, wherein the comprehensive performance index model and the total index model are both used to reflect communication performance;

[0070] Optionally, in this embodiment, this step is the process of the receiving end building a comprehensive performance model through test data and indicator models, so as to subsequently solve the model parameters through entropy weight method, least squares method and gradient ascent method, obtain the optimal transmission parameters, and lay a solid data foundation for subsequent data transmission.

[0071] Optionally, in this embodiment, the corresponding communication throughput, communication packet loss rate, communication transmission efficiency, communication delay and communication processing capability are determined based on the test data.

[0072] Optionally, the test data obtained in step S101 includes:

[0073] L: The total amount of data to be transmitted (bytes)

[0074] M: Maximum transmission unit of application layer data packets (MTU, bytes)

[0075] H0: Total Ethernet protocol overhead outside the application layer (bytes)

[0076] H: Application layer packet header size (bytes)

[0077] t: Each Ethernet frame transmission time (seconds)

[0078] p: Each Ethernet frame processing time (seconds)

[0079] B: Network bandwidth (bytes / second)

[0080] g: Minimum time interval between Ethernet frames (IFG, bytes)

[0081] q: number of packets received

[0082] Before obtaining the corresponding indicators based on the above test data, first construct the calculation formula and model corresponding to the indicators.

[0083] Specifically, the communication throughput T represents the amount of data successfully transmitted by the network per unit time. The calculation of throughput depends on the transmission and reception process of data packets, that is:

[0084] T=R (M+H), .

[0085] Specifically, the communication packet loss rate L represents the ratio of the number of data packets lost during the transmission process to the total number of data packets sent, that is, L = number of lost data packets / total number of sent data packets.

[0086] It can be understood that the communication throughput T and the communication packet loss rate L are obtained by experimentally measuring the amount of data successfully transmitted and the number of lost data packets during network transmission.

[0087] Specifically, communication transmission efficiency, build a communication transmission efficiency model:

[0088] The transmission efficiency E is defined as the ratio of the amount of effective data transmitted to the total amount of data transmitted.

[0089] Total number of Ethernet frames N:

[0090]

[0091] Total amount of data transmitted T:

[0092]

[0093] Transmission efficiency E:

[0094]

[0095] Specifically, communication delay, build a communication delay model:

[0096] The total delay D includes transmission time and processing time, as well as the minimum time interval between Ethernet frames.

[0097] Total transmission time T t :

[0098]

[0099] Total processing time T p :

[0100]

[0101] Total Ethernet frame interval IFG time T g :

[0102]

[0103] Total delay D:

[0104]

[0105] Specifically, communication processing capability, build a communication processing capability model:

[0106] The processing capacity is expressed as the number of Ethernet frames that can be processed per second. The number of Ethernet frames that can be processed per second R:

[0107]

[0108] After obtaining the above-mentioned communication throughput formula, communication packet loss rate formula, communication transmission efficiency model, communication delay model and communication processing capacity model, the actual test data is introduced into each formula and model to obtain the corresponding communication throughput index, communication packet loss rate index, communication transmission efficiency index, communication delay index and communication processing capacity index.

[0109] Then, for n samples and m indicators, let the value of the jth indicator of the ith sample be the value of the jth indicator. Taking the buffer area of ​​the receiving end B as 4096 bytes as an example, we can construct the following statistical test table:

[0110]

[0111] After obtaining the above statistical variable table and before the algorithm calculation, two comprehensive performance models are constructed:

[0112] Comprehensive performance index model Y0, in order to comprehensively consider transmission efficiency, delay and processing capacity, defines a comprehensive performance index. This index is a weighted average. The weight of transmission efficiency is: W1; the weight of delay is: W2; the weight of processing capacity is: W3. Comprehensive performance index Y0:

[0113]

[0114] Among them, E, D, and R are the above-mentioned communication transmission efficiency index, communication delay index, and communication processing capability index respectively.

[0115] The total index model Y1, because the throughput T and packet loss rate L can also comprehensively reflect the impact of the three dimensions of transmission efficiency, delay, and processing capacity in Y0 on communication performance, a total index Y1 is defined:

[0116] .

[0117] It can be understood that after step S102, we have obtained the entire statistical test table through the indicator model and the real test data, that is, when the sender sends data to the receiver according to different sample groups (M, g), the corresponding communication throughput indicator, communication packet loss rate indicator, communication transmission efficiency indicator, communication delay indicator and communication processing capacity indicator are measured. At the same time, in order to comprehensively consider the transmission efficiency, delay and processing capacity, a comprehensive performance indicator model Y0 and a total indicator model Y1 are constructed, which lays the foundation for the subsequent solution of the weight values ​​of Y0 and Y1 and the least squares fitting and gradient ascent algorithm to find the optimal mapping relationship between the transmission parameters M, g and the transmission performance Y0.

[0118] Step S103: Perform a weight calculation operation on the total index model according to a preset entropy weight method and the test data obtained after the communication test to obtain the corresponding weights of each indicator in the total index model, determine the corresponding total index formula according to the weights of each indicator, perform a fitting operation on the comprehensive performance index model according to the test data, the total index formula and a preset least squares algorithm to determine the corresponding comprehensive performance formula, iterate the comprehensive performance formula according to a preset gradient ascent algorithm to determine the corresponding optimal comprehensive performance index, determine the corresponding optimal transmission unit value and the optimal time interval according to the optimal comprehensive performance index, and send the optimal transmission unit value and the optimal time interval to the data sending end, so that the data sending end performs data transmission according to the optimal transmission unit value and the optimal time interval.

[0119] Optionally, in this embodiment, the purpose of this step is to find the mapping relationship between the transmission parameters M, g and the comprehensive performance Y0, and solve the optimal Y0 through the gradient ascent algorithm to obtain the corresponding optimal transmission parameters, perform data transmission according to the optimal transmission parameters, and improve the efficiency and reliability of simulated data transmission.

[0120] Optionally, in this embodiment, a weight calculation operation is performed on the total indicator model according to a preset entropy weight method and the test data obtained after the communication test to obtain the corresponding weights of each indicator in the total indicator model, and the corresponding total indicator formula is determined according to the weights of each indicator.

[0121] Specifically, the weight E of the above total index model Y1 is calculated according to the entropy weight method. T and W L .

[0122] Entropy is a physical concept in thermodynamics. It is a measure of the degree of chaos or disorder in a system. The larger the entropy, the more chaotic the system is (i.e., the less information it carries), and the smaller the entropy, the more ordered the system is (i.e., the more information it carries). Information entropy formula:

[0123]

[0124] Where H is the information entropy, q is the number of source messages, It is the message x i Probability of occurrence.

[0125] According to the definition of information entropy, for a certain indicator, the entropy value can be used to judge the degree of dispersion of a certain indicator. The smaller the information entropy value, the greater the degree of dispersion of the indicator, and the greater the impact of the indicator on the comprehensive evaluation (i.e., weight). If the values ​​of a certain indicator are all equal, then the indicator has no effect in the comprehensive evaluation. Therefore, the information entropy tool can be used to calculate the weight of each indicator and provide a basis for the comprehensive evaluation of multiple indicators.

[0126] Since the dimensions of various indicators are not consistent, the range transformation method is used for normalization before calculation to make heterogeneous indicators homogeneous. Differentiation is used for positive indicators such as throughput T and negative indicators such as packet loss rate L. For convenience, the normalized data is still recorded as X ij .

[0127] Positive indicators:

[0128]

[0129] Negative indicators:

[0130]

[0131] After normalizing the data in the table, calculate the weight of the j-th indicator sample value in turn:

[0132]

[0133] Calculate the entropy value of the j-th indicator, where ,satisfy :

[0134]

[0135] The weight of each indicator is calculated by the information entropy of each indicator, where K refers to the number of indicators, that is, K=m:

[0136]

[0137] Get the weight W T and W L After that, we can get the specific Y1 formula:

[0138]

[0139] Optionally, in this embodiment, the comprehensive performance indicator model is fitted according to the test data, the total indicator formula and a preset least squares algorithm to determine the corresponding comprehensive performance formula.

[0140] Specifically, after obtaining the specific Y1 formula, the value of Y1 under a certain sample (M, g) can be calculated by the Y1 formula according to the test table obtained in step S102. Within a certain range, Y0 and Y1 can be considered equivalent, and the value of Y1 is assigned to Y0. From the comprehensive performance indicators:

[0141]

[0142] At this point, the value of Y0 and the test data corresponding to the value of Y0 are known, and the specific values ​​of the E, D, and R indicators are obtained based on the test data and the indicator model.

[0143] Construct a data matrix from the statistical samples:

[0144]

[0145] The target vector Y0 is constructed from the statistical samples.

[0146] When the following conditions are met, the specific value of the weight is obtained:

[0147]

[0148] At this time, the expression of Y0 can minimize the sum of squared errors. The sum of squared errors is:

[0149]

[0150] At this point, the objective function has a specific form, namely the comprehensive performance formula:

[0151]

[0152] Optionally, in this embodiment, the comprehensive performance formula is iterated according to a preset gradient ascent algorithm to determine the corresponding optimal comprehensive performance indicator.

[0153] Specifically, calculate the gradient of the objective function with respect to M and g:

[0154]

[0155] in:

[0156]

[0157] Select the initial MTU value and initial IFG time, set the learning rate ɑ, and perform gradient ascent update to maximize Y0:

[0158]

[0159] Repeat the above steps until Y0 converges or reaches the maximum number of iterations. Y0 at this time is used as the optimal comprehensive performance indicator, which is the optimal value after comprehensively considering transmission efficiency, delay and processing capacity. The corresponding MTU value and IFG value are obtained according to Y0 at this time. The receiving end sends the MTU value and IFG value at this time to the sending end, so that the sending end communicates with the optimal MTU value and IFG value.

[0160] This example shows how this embodiment performs pre-negotiation before formal transmission between the sending end and the receiving end to determine the optimal transmission parameters, and performs data transmission according to the optimal parameters, thereby improving the efficiency and reliability of simulated data transmission.

[0161] From the above description, it can be seen that the adaptive real-time simulation data transmission method based on pre-negotiation provided in the embodiment of the present application can perform communication testing by sending data to the data receiving end according to the initial data transmission unit value and the preset time interval through the data sending end to obtain corresponding test data; the data receiving end calculates the communication throughput, communication packet loss rate, communication transmission efficiency, communication delay and communication processing capability according to the test data, and constructs a total index model and a comprehensive performance index model; the total index formula is calculated according to the entropy weight method, the test data is substituted into the total index formula to obtain the total index value, the comprehensive performance index model is fitted with the least squares algorithm according to the total index value, the comprehensive performance formula is determined, and the optimal comprehensive performance index is obtained according to the gradient ascent method. The data sending end performs data transmission according to the optimal comprehensive performance index, thereby improving the efficiency and reliability of simulated data transmission based on pre-negotiated parameters.

[0162] In one embodiment of the pre-negotiation-based adaptive real-time simulation data transmission method of the present application, see Figure 2 , and can also include the following:

[0163] Step S201: performing a buffer value calculation operation according to the receiving end to determine the corresponding maximum value of the receiving end buffer;

[0164] Step S202: performing a multiple value operation based on half of the maximum value of the receiving end buffer to determine the corresponding initial maximum transmission unit value, wherein the multiple value operation is to take the largest multiple of a preset integer within the range of half of the maximum value of the receiving end buffer.

[0165] Optionally, in this embodiment, the maximum transmission unit MTU (Maximum Transmission Unit) of the transmission data packet determines the maximum size of a single data packet. The initial test value of the maximum transmission unit of the transmission data packet is a maximum multiple of 128 bytes contained by half of the maximum value of the receiving end buffer. 128 bytes is a common DMA transmission block size, which can optimize DMA transmission, reduce the number of transmissions, improve transmission efficiency, and reduce CPU burden.

[0166] Optionally, the size of the receiving end buffer area should be set to avoid wasting the receiving end buffer area and maximize the use of the buffer area. Preferably, the size of the receiving end buffer area is 4096 bytes to ensure that the receiving end B can cache at least two data packets. The initial value of the application layer maximum transmission unit MTU is calculated by the receiving end B at the beginning to calculate the maximum multiple of 128 bytes contained in half of the maximum value of the receiving end buffer area, and send it to the sending end A, which performs subsequent tests based on this, wherein the sending end A is the simulation device end.

[0167] For example, taking the buffer area of ​​the receiving end B as 4096 bytes, the initial maximum transmission unit value is 2048.

[0168] Through step S202, this embodiment determines the initial maximum transmission unit value, laying a foundation for the subsequent sending end to perform communication testing according to the initial data.

[0169] In one embodiment of the pre-negotiation-based adaptive real-time simulation data transmission method of the present application, see Figure 3 , and can also include the following:

[0170] Step S301: sending the initial maximum transmission unit value to the data transmitting end, so that after receiving the initial maximum transmission unit value, the data transmitting end gradually decreases the initial maximum transmission unit value according to the preset integer to determine a plurality of corresponding maximum transmission unit values, gradually increases the preset initial time interval according to a preset frame interval increment to determine a plurality of corresponding time intervals, and performs sample combination operations on the plurality of maximum transmission unit values ​​and the plurality of time intervals to determine a plurality of sample groups;

[0171] Step S302: Perform communication test operations with the data receiving end according to the multiple sample groups and the preset number of communications, and determine the test data corresponding to each sample group, wherein the test data includes the total amount of data to be transmitted, the number of received data packets, the maximum transmission unit, the sum of the Ethernet protocol overhead outside the application layer, the application layer data packet header size, the transmission time of each Ethernet frame, the processing time of each Ethernet frame, the network bandwidth and the minimum time interval.

[0172] Optionally, in this embodiment, after determining the initial maximum transmission unit value, the transmitter A starts the communication test. Specifically, the transmitter A determines multiple MTU samples based on the initial maximum transmission unit value, with a step size of 128 bytes, and the MTU value is gradually reduced to a minimum of 128 bytes. After the MTU sample is determined, a corresponding time interval group is specified for each MTU sample. Preferably, the time interval group gradually increases in the range of 12 bytes to 20 bytes. Each MTU sample (M) and the corresponding time interval (g) are combined into a sample group (M, g). Preferably, each group (M, g) is tested 2 times. 16 times to obtain test data.

[0173] The test data includes:

[0174] L: The total amount of data to be transmitted (bytes)

[0175] M: Maximum transmission unit of application layer data packets (MTU, bytes)

[0176] H0: Total Ethernet protocol overhead outside the application layer (bytes)

[0177] H: Application layer packet header size (bytes)

[0178] t: Each Ethernet frame transmission time (seconds)

[0179] p: Each Ethernet frame processing time (seconds)

[0180] B: Network bandwidth (bytes / second)

[0181] g: Minimum time interval between Ethernet frames (IFG, bytes)

[0182] q: number of packets received

[0183] Through step S302, this embodiment constructs sample groups and obtains test data under each sample group, laying a foundation for subsequently obtaining sample indicators.

[0184] In one embodiment of the pre-negotiation-based adaptive real-time simulation data transmission method of the present application, see Figure 4 , and can also include the following:

[0185] Step S401: performing a model building operation according to a preset total amount of data to be transmitted, a preset maximum transmission unit, a preset sum of Ethernet protocol overhead outside the application layer, and a preset application layer data packet header size to determine a corresponding communication transmission efficiency model;

[0186] Step S402: performing a model building operation according to a preset total amount of data to be transmitted, a preset maximum transmission unit, a preset transmission time of each Ethernet frame, a preset processing time of each Ethernet frame, and a preset minimum time interval, to determine a corresponding communication delay model;

[0187] Step S403: Perform a model building operation according to the preset processing time of each Ethernet frame and the preset minimum time interval to determine the corresponding communication processing capability model.

[0188] Optionally, in this embodiment, this step pre-builds a sample indicator model for bringing real test data into the sample indicator model to obtain corresponding sample indicators, thereby laying a data foundation for the subsequent establishment of a statistical test table.

[0189] Specifically, communication transmission efficiency, build a communication transmission efficiency model:

[0190] The transmission efficiency E is defined as the ratio of the amount of effective data transmitted to the total amount of data transmitted.

[0191] Total number of Ethernet frames N:

[0192]

[0193] Total amount of data transmitted T:

[0194]

[0195] Transmission efficiency E:

[0196]

[0197] Specifically, communication delay, build a communication delay model:

[0198] The total delay D includes transmission time and processing time, as well as the minimum time interval between Ethernet frames.

[0199] Total transmission time T t :

[0200]

[0201] Total processing time T p :

[0202]

[0203] Total Ethernet frame interval IFG time T g :

[0204]

[0205] Total delay D:

[0206]

[0207] Specifically, communication processing capability, build a communication processing capability model:

[0208] The processing capacity is expressed as the number of Ethernet frames that can be processed per second. The number of Ethernet frames that can be processed per second R:

[0209]

[0210] Through step S403, the present embodiment successfully constructs the indicator model. Substituting the real test data into the indicator model can obtain the corresponding indicators, thus laying a foundation for the subsequent construction of the statistical test table.

[0211] In one embodiment of the pre-negotiation-based adaptive real-time simulation data transmission method of the present application, see Figure 5 , and can also include the following:

[0212] Step S501: determining the corresponding communication throughput according to the test data and a preset communication throughput formula;

[0213] Step S502: determining a corresponding communication packet loss rate according to the test data and a preset communication packet loss rate formula;

[0214] Step S503: determining the corresponding communication transmission efficiency according to the test data and the communication transmission efficiency model;

[0215] Step S504: determining a corresponding communication delay according to the test data and the communication delay model;

[0216] Step S505: Determine the corresponding communication processing capability according to the test data and the communication processing capability model.

[0217] Optionally, in this embodiment, the communication throughput T represents the amount of data successfully transmitted by the network in a unit time. The calculation of the throughput depends on the transmission and reception process of the data packet, that is:

[0218] T=R (M+H), .

[0219] Substitute M, H, p, and g in the test data into the communication throughput formula to obtain the communication throughput index.

[0220] Optionally, in this embodiment, the communication packet loss rate L represents the ratio of the number of data packets lost during the transmission process to the total number of data packets sent, that is, L = the number of lost data packets / the total number of sent data packets. According to q in the test data, the communication packet loss rate formula is substituted to obtain the communication packet loss rate indicator.

[0221] Optionally, in this embodiment, L, M, H, and H0 in the test data are substituted into the transmission efficiency model E to obtain a transmission efficiency index.

[0222] Optionally, in this embodiment, L, M, t, p, and g in the test data are substituted into the communication delay D to obtain a communication delay index.

[0223] Optionally, in this embodiment, p and g in the test data are substituted into the communication processing capability model R to obtain a communication processing capability indicator.

[0224] Through step S505, this embodiment successfully obtains five communication indicators corresponding to the communication parameter sample group. The communication indicators are used to reflect the communication efficiency and lay a solid foundation for subsequently finding the optimal communication parameters.

[0225] In one embodiment of the pre-negotiation-based adaptive real-time simulation data transmission method of the present application, see Figure 6 , and can also include the following:

[0226] Step S601: performing an information entropy calculation operation on the communication throughput and the communication packet loss rate obtained after the communication test to determine corresponding communication throughput information entropy and communication packet loss rate information entropy;

[0227] Step S602: Determine a corresponding communication throughput weight and a communication packet loss rate weight according to the communication throughput information entropy and the communication packet loss rate information entropy;

[0228] Step S603: Substituting the communication throughput weight and the communication packet loss rate weight into the total indicator model to determine a corresponding total indicator formula.

[0229] Optionally, in this embodiment, the weight E of the above-mentioned total indicator model Y1 is calculated according to the entropy weight method. T and W L .

[0230] First, the range transformation method is used to perform normalization before the calculation to make the heterogeneous indicators homogeneous. Differentiation is used for positive indicators such as throughput T and negative indicators such as packet loss rate L. For convenience, the normalized data is still recorded as X ij .

[0231] After normalizing the data in the table, calculate the weight of the j-th indicator sample value in turn:

[0232]

[0233] Calculate the entropy value of the j-th indicator, where ,satisfy :

[0234]

[0235] The weight of each indicator is calculated by the information entropy of each indicator, where K refers to the number of indicators, that is, K=m:

[0236]

[0237] Get the weight W T and W L After that, we can get the specific Y1 formula:

[0238]

[0239] Through step S603, this embodiment successfully obtains the weight of the total index model Y1 and derives the Y1 formula, laying a foundation for subsequently using the Y1 formula to obtain the comprehensive performance index Y0 formula.

[0240] In one embodiment of the pre-negotiation-based adaptive real-time simulation data transmission method of the present application, see Figure 7 , and can also include the following:

[0241] Step S701: Substituting the communication throughput and the communication packet loss rate obtained according to the test data into the total index formula to determine the corresponding total index value, assigning the total index value to the comprehensive performance index model to determine the corresponding comprehensive performance index value;

[0242] Step S702: performing a target vector construction operation according to the comprehensive performance index value to determine a corresponding target vector, wherein the comprehensive performance index value corresponds to the test data;

[0243] Step S703: performing a matrix construction operation on the communication transmission efficiency, the communication delay, and the communication processing capability obtained according to the test data to determine a corresponding data matrix;

[0244] Step S704: Perform a fitting operation according to a preset least squares algorithm, the data matrix and the target vector to determine the weights of each indicator in the corresponding comprehensive performance indicator model, and perform a substitution operation on the comprehensive performance indicator model according to the weights of each indicator in the comprehensive performance indicator model to determine the corresponding comprehensive performance formula.

[0245] Optionally, in this embodiment, after obtaining a specific Y1 formula, the value of Y1 under a certain sample (M, g) can be calculated by the Y1 formula according to the test table obtained in step S102. Within a certain range, Y0 and Y1 can be considered equivalent, and the value of Y1 is assigned to Y0. Based on the comprehensive performance index:

[0246]

[0247] At this point, the value of Y0 and the test data corresponding to the value of Y0 are known, and the specific values ​​of the E, D, and R indicators are obtained based on the test data and the indicator model.

[0248] Construct a data matrix from the statistical samples:

[0249]

[0250] The target vector Y0 is constructed from the statistical samples.

[0251] When the following conditions are met, the specific value of the weight is obtained:

[0252]

[0253] At this time, the expression of Y0 can minimize the sum of squared errors. The sum of squared errors is:

[0254]

[0255] At this point, the objective function has a specific form, namely the comprehensive performance formula:

[0256]

[0257] Through step S704, this embodiment successfully obtains the comprehensive performance index, laying a solid foundation for subsequently obtaining the maximized comprehensive performance value through the gradient ascent algorithm.

[0258] In order to improve the efficiency and reliability of simulated data transmission based on pre-negotiation parameters, the present application provides an embodiment of a pre-negotiation-based adaptive real-time simulated data transmission device for implementing all or part of the content of the pre-negotiation-based adaptive real-time simulated data transmission method, see Figure 8 The pre-negotiation-based adaptive real-time simulation data transmission device specifically includes the following contents:

[0259] The communication test module 10 is used to determine the initial maximum transmission unit value of the corresponding transmission data packet according to the buffer size, and send the initial maximum transmission unit value to the data sending end, so that the data sending end performs a communication test operation with the data receiving end according to the initial maximum transmission unit value and a preset initial time interval after receiving the initial maximum transmission unit value, and determines the corresponding test data;

[0260] An indicator model determination module 20 is used to determine the corresponding communication throughput, communication packet loss rate, communication transmission efficiency, communication delay and communication processing capacity according to the test data, perform an abstract model construction operation according to the communication throughput and the communication packet loss rate, determine the corresponding total indicator model, perform an abstract model construction operation according to the communication transmission efficiency, the communication delay and the communication processing capacity, and determine the corresponding comprehensive performance indicator model, wherein the comprehensive performance indicator model and the total indicator model are both used to reflect communication performance;

[0261] The optimal comprehensive performance index determination module 30 is used to perform a weight calculation operation on the total index model according to a preset entropy weight method and the test data obtained after the communication test, to obtain the corresponding weights of each indicator in the total index model, to determine the corresponding total index formula according to the weights of each indicator, to perform a fitting operation on the comprehensive performance index model according to the test data, the total index formula and a preset least squares algorithm, to determine the corresponding comprehensive performance formula, to iterate the comprehensive performance formula according to a preset gradient ascent algorithm, to determine the corresponding optimal comprehensive performance index, to determine the corresponding optimal transmission unit value and the optimal time interval according to the optimal comprehensive performance index, and to send the optimal transmission unit value and the optimal time interval to the data sending end, so that the data sending end performs data transmission according to the optimal transmission unit value and the optimal time interval.

[0262] It can be seen from the above description that the adaptive real-time simulated data transmission device based on pre-negotiation provided in the embodiment of the present application can improve the efficiency and reliability of simulated data transmission based on pre-negotiation parameters.

[0263] From a hardware perspective, in order to improve the efficiency and reliability of simulated data transmission based on pre-negotiation parameters, the present application provides an embodiment of an electronic device for implementing all or part of the content of the pre-negotiation-based adaptive real-time simulated data transmission method, and the electronic device specifically includes the following content:

[0264] Processor, memory, communication interface and bus; wherein the processor, memory and communication interface communicate with each other through the bus; the communication interface is used to realize information transmission between the adaptive real-time simulation data transmission method based on pre-negotiation and related devices such as core business systems, user terminals and related databases; the logic controller can be a desktop computer, a tablet computer and a mobile terminal, etc., but the present embodiment is not limited thereto. In the present embodiment, the logic controller can be implemented with reference to the embodiment of the adaptive real-time simulation data transmission method based on pre-negotiation and the embodiment of the adaptive real-time simulation data transmission method based on pre-negotiation in the embodiment, and the contents thereof are incorporated herein, and the repeated parts are not repeated.

[0265] It is understandable that the user terminal may include a smart phone, a tablet electronic device, a network set-top box, a portable computer, a desktop computer, a personal digital assistant (PDA), a vehicle-mounted device, a smart wearable device, etc. Among them, the smart wearable device may include smart glasses, a smart watch, a smart bracelet, etc.

[0266] In practical applications, part of the pre-negotiation-based adaptive real-time simulation data transmission method can be performed on the electronic device side as described above, or all operations can be completed in the client device. Specifically, it can be selected according to the processing capability of the client device and the limitations of the user's usage scenario. This application does not limit this. If all operations are completed in the client device, the client device may also include a processor.

[0267] The client device may have a communication module (i.e., a communication unit) that can communicate with a remote server to achieve data transmission with the server. The server may include a server on the task scheduling center side, and other implementation scenarios may also include a server on an intermediate platform, such as a server on a third-party server platform that has a communication link with the task scheduling center server. The server may include a single computer device, or a server cluster consisting of multiple servers, or a server structure of a distributed device.

[0268] Fig. 9 FIG. 9 is a schematic block diagram of the system structure of the electronic device 9600 according to an embodiment of the present application. Fig. 9 As shown, the electronic device 9600 may include a central processor 9100 and a memory 9140; the memory 9140 is coupled to the central processor 9100. It is worth noting that Fig. 9 is exemplary; other types of structures may also be used to supplement or replace this structure to implement telecommunication functions or other functions.

[0269] In one embodiment, the function of the adaptive real-time simulation data transmission method based on pre-negotiation can be integrated into the central processing unit 9100. The central processing unit 9100 can be configured to perform the following control:

[0270] Step S101: determining an initial maximum transmission unit value of a corresponding transmission data packet according to the size of the buffer area, and sending the initial maximum transmission unit value to the data transmitting end, so that after receiving the initial maximum transmission unit value, the data transmitting end performs a communication test operation with the data receiving end according to the initial maximum transmission unit value and a preset initial time interval, and determines corresponding test data;

[0271] Step S102: determining the corresponding communication throughput, communication packet loss rate, communication transmission efficiency, communication delay and communication processing capability according to the test data, performing an abstract model construction operation according to the communication throughput and the communication packet loss rate, determining the corresponding total index model, performing an abstract model construction operation according to the communication transmission efficiency, the communication delay and the communication processing capability, and determining the corresponding comprehensive performance index model, wherein the comprehensive performance index model and the total index model are both used to reflect communication performance;

[0272] Step S103: Perform a weight calculation operation on the total index model according to a preset entropy weight method and the test data obtained after the communication test to obtain the corresponding weights of each indicator in the total index model, determine the corresponding total index formula according to the weights of each indicator, perform a fitting operation on the comprehensive performance index model according to the test data, the total index formula and a preset least squares algorithm to determine the corresponding comprehensive performance formula, iterate the comprehensive performance formula according to a preset gradient ascent algorithm to determine the corresponding optimal comprehensive performance index, determine the corresponding optimal transmission unit value and the optimal time interval according to the optimal comprehensive performance index, and send the optimal transmission unit value and the optimal time interval to the data sending end, so that the data sending end performs data transmission according to the optimal transmission unit value and the optimal time interval.

[0273] It can be seen from the above description that the electronic device provided in the embodiment of the present application can improve the efficiency and reliability of simulated data transmission based on pre-negotiated parameters.

[0274] It should be understood by those skilled in the art that embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0275] The present invention uses specific embodiments to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A method for transmitting adaptive real-time simulated data based on pre-negotiation, characterized in that: Applied to a data receiving end, the data receiving end is communicatively connected with a preset data sending end, the method comprises: Determine an initial maximum transmission unit value of the corresponding transmission data packet according to the size of the buffer area, and send the initial maximum transmission unit value to the data sending end, so that the data sending end performs a communication test operation with the data receiving end according to the initial maximum transmission unit value and a preset initial time interval after receiving the initial maximum transmission unit value, and determines corresponding test data; Determine the corresponding communication throughput, communication packet loss rate, communication transmission efficiency, communication delay and communication processing capacity according to the test data, perform an abstract model construction operation according to the communication throughput and the communication packet loss rate, determine the corresponding total index model, perform an abstract model construction operation according to the communication transmission efficiency, the communication delay and the communication processing capacity, and determine the corresponding comprehensive performance index model, wherein the comprehensive performance index model and the total index model are both used to reflect communication performance; A weight calculation operation is performed on the total index model according to a preset entropy weight method and the test data obtained after the communication test to obtain the corresponding weights of each index in the total index model; a corresponding total index formula is determined according to the weights of each index; a fitting operation is performed on the comprehensive performance index model according to the test data, the total index formula and a preset least squares algorithm to determine the corresponding comprehensive performance formula; an iterative operation is performed on the comprehensive performance formula according to a preset gradient ascent algorithm to determine the corresponding optimal comprehensive performance index; a corresponding optimal transmission unit value and an optimal time interval are determined according to the optimal comprehensive performance index; and the optimal transmission unit value and the optimal time interval are sent to the data sending end so that the data sending end transmits data according to the optimal transmission unit value and the optimal time interval.

2. The method for transmitting data based on pre-negotiation in real-time simulation according to claim 1, characterized in that: The step of determining the corresponding initial maximum transmission unit value according to the buffer size includes: Performing a buffer value calculation operation on the receiving end to determine a corresponding maximum value of the receiving end buffer; A multiple value operation is performed based on half of the maximum value of the receiving end buffer area to determine the corresponding initial maximum transmission unit value, wherein the multiple value operation is to take the largest multiple of a preset integer within the range of half of the maximum value of the receiving end buffer area.

3. The method for transmitting data based on pre-negotiation in real-time according to claim 1, characterized in that: The sending of the initial maximum transmission unit value to the data transmitting end so that the data transmitting end performs a communication test operation with the data receiving end according to the initial maximum transmission unit value and a preset initial time interval after receiving the initial maximum transmission unit value, and determines corresponding test data, includes: The initial maximum transmission unit value is sent to the data transmitting end, so that after receiving the initial maximum transmission unit value, the data transmitting end gradually decreases the initial maximum transmission unit value according to a preset integer to determine a corresponding plurality of maximum transmission unit values, gradually increases the preset initial time interval according to a preset frame interval increment to determine a corresponding plurality of time intervals, and performs sample combination operations on the plurality of maximum transmission unit values ​​and the plurality of time intervals to determine a plurality of sample groups; A communication test operation is performed with the data receiving end according to the multiple sample groups and the preset number of communications, and test data corresponding to each sample group is determined, wherein the test data includes the total amount of data to be transmitted, the number of received data packets, the maximum transmission unit, the sum of the Ethernet protocol overhead outside the application layer, the size of the application layer data packet header, the transmission time of each Ethernet frame, the processing time of each Ethernet frame, the network bandwidth and the minimum time interval.

4. The method for transmitting data based on pre-negotiation in real-time according to claim 1, characterized in that: Before determining the corresponding communication throughput, communication packet loss rate, communication transmission efficiency, communication delay and communication processing capacity according to the test data, the method includes: A model building operation is performed according to a preset total amount of data to be transmitted, a preset maximum transmission unit, a preset sum of Ethernet protocol overhead outside the application layer, and a preset application layer data packet header size to determine a corresponding communication transmission efficiency model; Perform a model building operation according to a preset total amount of data to be transmitted, a preset maximum transmission unit, a preset transmission time of each Ethernet frame, a preset processing time of each Ethernet frame, and a preset minimum time interval to determine a corresponding communication delay model; A model building operation is performed according to the preset processing time of each Ethernet frame and the preset minimum time interval to determine the corresponding communication processing capability model.

5. The method for transmitting data based on pre-negotiation in real-time according to claim 1, characterized in that: Determining the corresponding communication throughput, communication packet loss rate, communication transmission efficiency, communication delay and communication processing capability according to the test data includes: Determine the corresponding communication throughput according to the test data and a preset communication throughput formula; Determine the corresponding communication packet loss rate according to the test data and a preset communication packet loss rate formula; Determining the corresponding communication transmission efficiency according to the test data and the preset communication transmission efficiency model; Determining corresponding communication delays according to the test data and a preset communication delay model; The corresponding communication processing capability is determined according to the test data and a preset communication processing capability model.

6. The method for transmitting data based on adaptive real-time simulation based on pre-negotiation according to claim 1, characterized in that: The weight calculation operation is performed on the total index model according to the preset entropy weight method and the test data obtained after the communication test to obtain the weight of each indicator in the corresponding total index model, and the corresponding total index formula is determined according to the weight of each indicator, including: Performing an information entropy calculation operation on the communication throughput and the communication packet loss rate obtained after the communication test to determine corresponding communication throughput information entropy and communication packet loss rate information entropy; Determine the corresponding communication throughput weight and communication packet loss rate weight according to the communication throughput information entropy and the communication packet loss rate information entropy; The communication throughput weight and the communication packet loss rate weight are substituted into the total indicator model to determine a corresponding total indicator formula.

7. The method for transmitting data based on pre-negotiation in real-time according to claim 1, characterized in that: The fitting operation is performed on the comprehensive performance index model according to the test data, the total index formula and a preset least squares algorithm to determine the corresponding comprehensive performance formula, including: Substituting the communication throughput and the communication packet loss rate obtained according to the test data into the total index formula to determine the corresponding total index value, assigning the total index value to the comprehensive performance index model to determine the corresponding comprehensive performance index value; Performing a target vector construction operation according to the comprehensive performance index value to determine a corresponding target vector, wherein the comprehensive performance index value corresponds to the test data; Performing a matrix construction operation on the communication transmission efficiency, the communication delay, and the communication processing capability obtained according to the test data to determine a corresponding data matrix; A fitting operation is performed according to a preset least squares algorithm, the data matrix and the target vector to determine the weight of each indicator in the corresponding comprehensive performance indicator model, and the comprehensive performance indicator model is substituted according to the weight of each indicator in the comprehensive performance indicator model to determine the corresponding comprehensive performance formula.

8. An adaptive real-time simulation data transmission device based on pre-negotiation, characterized in that: The device comprises: A communication test module, used to determine an initial maximum transmission unit value of a corresponding transmission data packet according to a buffer size, and send the initial maximum transmission unit value to a data transmitting end, so that after receiving the initial maximum transmission unit value, the data transmitting end performs a communication test operation with a data receiving end according to the initial maximum transmission unit value and a preset initial time interval, and determines corresponding test data; An indicator model determination module is used to determine the corresponding communication throughput, communication packet loss rate, communication transmission efficiency, communication delay and communication processing capacity according to the test data, perform an abstract model construction operation according to the communication throughput and the communication packet loss rate, and determine the corresponding total indicator model, perform an abstract model construction operation according to the communication transmission efficiency, the communication delay and the communication processing capacity, and determine the corresponding comprehensive performance indicator model, wherein the comprehensive performance indicator model and the total indicator model are both used to reflect communication performance; The optimal comprehensive performance index determination module is used to perform a weight calculation operation on the total index model according to a preset entropy weight method and the test data obtained after the communication test, obtain the corresponding weight of each indicator in the total index model, determine the corresponding total index formula according to the weight of each indicator, perform a fitting operation on the comprehensive performance index model according to the test data, the total index formula and a preset least squares algorithm, determine the corresponding comprehensive performance formula, iterate the comprehensive performance formula according to a preset gradient ascent algorithm, determine the corresponding optimal comprehensive performance index, determine the corresponding optimal transmission unit value and the optimal time interval according to the optimal comprehensive performance index, and send the optimal transmission unit value and the optimal time interval to the data sending end, so that the data sending end performs data transmission according to the optimal transmission unit value and the optimal time interval.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the pre-negotiation-based adaptive real-time simulation data transmission method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the pre-negotiation-based adaptive real-time simulation data transmission method according to any one of claims 1 to 7 are implemented.

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