Real-time multimedia message transmission method based on 5G network

Abstract

The invention discloses a real-time multimedia message transmission method based on a 5G network, which relates to the technical field of data transmission, is used for improving the problems that part of verification and algorithms cannot identify data repetition and the like, and comprises the following steps: detecting the transmission distance and the transmission data volume of a transmission channel, and calculating the error rate of transmission data through a grading method; when the error rate of the transmission data is higher than a threshold value, calculating the check sum of the transmission data when the transmission data is transmitted out and received by utilizing an accumulation and check algorithm, judging whether the transmission is wrong or not through check, and when the check sum is consistent, obtaining the data source and the data updating frequency of the transmission data; the data repetition degree is analyzed through fuzzy reasoning according to the data source and the updating frequency, if the data repetition degree is high, the data repetition rate is calculated, different verification and algorithms are provided for a user to select according to the data repetition degree, and whether the data repetition problem occurs or not is judged according to the verification and algorithms; and when the data are repeated, a data repetition rate is given to facilitate subsequent analysis processing.

Description

Technical Field

[0001] The present invention relates to the field of data transmission technology, and more specifically, to a real-time multimedia message transmission method based on a 5G network. Background Art

[0002] Data transmission technology is the process of transferring data from one device or system to another. When data transmission technology is applied to multimedia message transmission, it makes the transmission of multimedia messages more efficient, convenient, secure and smooth, providing great convenience for modern life.

[0003] The prior art has the following deficiencies:

[0004] When multimedia information is transmitted in a network channel, errors such as garbled characters or information duplication may occur. Most transmission mechanisms will calculate and check the outgoing information and the received information respectively. When the checksum calculation results are inconsistent, it is judged that an error has occurred in the transmission of the multimedia information. However, when data duplication occurs in the multimedia information, some checksum algorithms can also obtain the same calculation results, resulting in problems such as inability to identify data duplication in the multimedia information and data analysis errors. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a real-time multimedia message transmission method based on a 5G network, which selects different checks and algorithms by analyzing the error rate and repetition rate of the transmitted data to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A real-time multimedia message transmission method based on a 5G network comprises the following steps:

[0008] Step S1: collecting transmission distances and transmission data volumes of multiple transmission channels for preprocessing;

[0009] Step S2: setting an error threshold according to the pre-processed transmission distance and the amount of transmission data and calculating the transmission data error rate. When the transmission data error rate exceeds the error threshold, using the accumulation and verification algorithm to preliminarily determine whether the transmission is erroneous;

[0010] Step S3: When it is preliminarily determined that the transmission is not wrong, the data source and update frequency of the transmission data are collected, and the data duplication degree is analyzed based on the data source and update frequency. If the data duplication degree is high, the data duplication rate is calculated;

[0011] Step S4: Select a bitmap algorithm according to the degree of data duplication or apply the data repetition rate to the BLAKE2 algorithm to detect whether the transmitted data has a data duplication problem.

[0012] In a preferred embodiment, in step S1, the transmission distance of the transmission channel cannot be directly obtained, and the system represents the result obtained by calculating the physical distance between two transmission devices and the network signal strength where the two transmission devices are located and performing graded summation; the transmission data volume of the transmission channel is obtained by detecting the size of the storage space occupied by the transmission data in the system.

[0013] In a preferred embodiment, in step S1, the system sets up multiple groups of transmission equipment, detects the transmission distance and transmission data volume of each group of transmission channels respectively, and performs normalization processing to obtain multiple groups of transmission distance coefficients and transmission volume coefficients.

[0014] In a preferred embodiment, in step S2, the processed transmission distance coefficients are combined into a transmission distance data set, and the transmission volume coefficients are combined into a transmission volume data set. The specific steps of setting the error threshold are as follows:

[0015] The same processing is performed on the two data sets. The data set is used as the analysis data set. The analysis data set is divided into two parts of equal number. The average values ​​of the two data sets are calculated and compared respectively. The part with the larger average value is selected as the new round of analysis data set. The new round of analysis data set is then divided into two parts of equal number to calculate the average value. The part with the smaller average value is selected as the new round of analysis data set. The operation on the data set is repeated alternately by taking the larger and smaller values ​​until the last data is left. The average value of the data obtained after processing the two data sets is set as the error threshold.

[0016] In a preferred embodiment, in step S2, the system calculates the transmission distance coefficient and the transmission volume coefficient of the transmission data to be tested and takes the average value as the transmission data error rate. When the transmission data error rate exceeds the error threshold, the system determines that the transmission data to be tested is prone to errors and uses the accumulation and verification algorithm to make an initial judgment on the transmission data.

[0017] In a preferred embodiment, in step S3, the data source obtains all data sources of the transmitted data by accessing the metadata field in the database table, and records the number of data sources of the transmitted data; when obtaining the data update frequency, the number of supplementary transmissions of the transmitted data is recorded by setting a time period to reflect the data update frequency.

[0018] In a preferred embodiment, in step S3, the specific steps of using fuzzy reasoning when analyzing the degree of data duplication are as follows:

[0019] The number of data sources and the number of supplementary transmissions are defined as input variables and divided into fuzzy sets;

[0020] The data duplication degree is defined as the output variable and divided into fuzzy sets;

[0021] Formulate fuzzy rules to describe the impact of the number of data sources and the number of supplementary transmissions on the degree of data duplication;

[0022] Perform fuzzy reasoning based on fuzzy rules to determine the degree of data duplication.

[0023] In a preferred embodiment, in step S3, when calculating the data repetition rate, the number of data sources of the transmitted data and the number of supplementary transmission times are summed to obtain a normalized parameter, which is then calculated using an exponential normalization formula based on the normalized parameter.

[0024] In a preferred embodiment, in step S4, when the data repetition degree is low, the system uses a bitmap algorithm to detect the transmission data; when the data repetition degree is high, the system uses a BLAKE2 algorithm to detect the transmission data;

[0025] If data duplication occurs in the transmitted data using the BLAKE2 algorithm, the data duplication rate of the transmitted data is given; if data duplication does not occur, the transmitted data is recorded.

[0026] The technical effects and advantages of a real-time multimedia message transmission method based on 5G network of the present invention are as follows:

[0027] The present invention analyzes the error rate of transmission data by detecting the transmission distance and the amount of transmission data of the transmission channel. When the error rate of transmission data is higher than a threshold value, a cumulative sum check algorithm is used to respectively calculate the checksum of the transmission data when it is transmitted and received. A large amount of calculation cost is saved by calculating the error rate of transmission data and the cumulative sum check algorithm. Whether the transmission is erroneous is determined by the checksum. When the checksum is consistent, the data source and update frequency of the transmission data are collected, and the data duplication degree is analyzed based on the data source and update frequency. If the data duplication degree is high, the data duplication rate is calculated, and different checksum algorithms are provided for users to choose according to the data duplication degree. Finally, the calculation result of the checksum algorithm is used to determine whether the data duplication problem occurs. The calculation cost is saved by providing a suitable checksum algorithm, and the judgment accuracy is improved while analyzing the transmission error type to facilitate the subsequent accurate correction of the error. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a schematic diagram of a real-time multimedia message transmission method based on a 5G network in the present invention. DETAILED DESCRIPTION

[0029] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] The present invention analyzes the error rate of transmission data by detecting the transmission distance and the amount of transmission data of the transmission channel. When the error rate of transmission data is higher than a threshold, a cumulative sum checksum algorithm is used to respectively calculate the checksum of the transmission data when it is transmitted and received. Whether the transmission is erroneous is determined by the checksum. When the checksum is inconsistent, it is determined that an error occurs in the transmission data transmission. When the checksum is consistent, the data source and data update frequency of the transmission data are obtained. The data repetition degree is analyzed by fuzzy reasoning based on the data source and the update frequency. If the data repetition degree is high, the data repetition rate is calculated. Different checksum algorithms are provided for users to choose according to the data repetition degree. Finally, whether the data repetition problem occurs is determined by the calculation result of the checksum algorithm. When the data is repeated, the data repetition rate is given to facilitate subsequent analysis and processing.

[0031] Embodiment, a real-time multimedia message transmission method based on 5G network, such as Figure 1 As shown, the following steps are included:

[0032] Step S1: collecting transmission distances and transmission data volumes of multiple transmission channels for preprocessing;

[0033] Step S2: setting an error threshold according to the pre-processed transmission distance and transmission data volume and calculating the transmission data error rate. When the transmission data error rate exceeds the error threshold, using the accumulation and verification algorithm to preliminarily determine whether the transmission is erroneous;

[0034] Step S3: When it is preliminarily determined that the transmission is not wrong, the data source and update frequency of the transmission data are collected, and the data duplication degree is analyzed based on the data source and update frequency. If the data duplication degree is high, the data duplication rate is calculated;

[0035] Step S4: Select a bitmap algorithm according to the degree of data duplication or apply the data repetition rate to the BLAKE 2 algorithm to detect whether the transmitted data has a data duplication problem.

[0036] The specific implementation is as follows:

[0037] In step S1, the transmission distance of the transmission channel cannot be obtained directly. The system obtains the address of the outgoing device and the address of the receiving device by connecting to the positioning system and calculates the physical distance between the two devices. It then opens a command line to prompt the user to enter a specified command to view the device network environment and receive the network signal strength entered by the user.

[0038] After determining the physical distance and receiving the network signal strength, the system uses a grading method to grade the physical distance and network signal, obtains the set value and sums it up, and uses the calculated result as the transmission distance coefficient of the transmission channel. The transmission distance coefficient reflects the transmission distance of the transmission channel.

[0039] The grading method is to grade data according to its size. Taking the physical distance in this example as an example, the system calculates the physical distance between multiple groups of devices, and grades the calculated physical distance data by percentage, sets different level coefficients for different levels of physical distance data, and after calculating the physical distance between the detection devices, uses the level coefficient of the level interval as a reference coefficient for subsequent analysis and processing. For example, if the percentage is set to 20%, the system will arrange the calculated physical distances between multiple groups of devices from small to large, and divide them into 5 groups with a percentage of 20%, each group corresponding to a level, and set the level coefficients of the 5 groups in the order of arrangement to: 0.3, 0.4, 0.5, 0.6 and 0.7. The network signal strength is similarly pre-processed and the transmission distance coefficient is calculated.

[0040] It needs to be explained that the percentage used in grading can be set according to actual conditions, and the setting of the level coefficient should satisfy the corresponding relationship of the parameters. The smaller the physical distance between the two devices or the greater the network signal strength, the smaller the transmission distance coefficient of its transmission channel. Therefore, when setting the level coefficient, the greater the physical distance, the greater the level coefficient, and the smaller the network signal strength, the greater the level coefficient.

[0041] The system detects the transmission data before it is transmitted to determine the size of the transmission data, that is, how much storage space the system occupies. After calculating the transmission distance coefficient of each group of equipment, the system detects each group of transmission data and obtains the transmission data volume of each group. The transmission data volume of each group is divided by the largest transmission data volume of all groups. The calculation result is used as the transmission volume coefficient.

[0042] It should be noted that in step S1, the number of collection combinations can be set in the system, and the system will obtain the calculation data corresponding to the number of collection combinations. For example, if the number of collection combinations is set to 10, the system will collect 10 groups of devices and calculate the transmission distance coefficient and the amount of transmission data of the transmission channel of each group of devices. In this example, each group has two devices, and the amount of transmission data can be obtained by accessing the property page of viewing the transmission data.

[0043] In step S2, the system merges multiple transmission distance coefficients and transmission volume coefficients into a transmission distance data set and a transmission volume data set, and sets an error threshold through the transmission distance data set and the transmission volume data set. The specific method for setting the error threshold is as follows:

[0044] The system uses the transmission distance data set as the analysis data set, randomly arranges the data in the analysis data set, counts the number of data in the analysis data set, divides the analysis data set into two parts with the same number of data, calculates the data averages in the two data sets respectively and compares them, and screens out the part with the larger data average as a new round of analysis data set; the new round of analysis data set calculates the data averages in the two data sets in the same way, compares them, and screens out the part with the smaller data average as a new round of analysis data set, alternately taking the data sets with larger data averages and smaller data averages as the analysis data sets, and repeats the operation until only the last data is left in the analysis data set, that is, the last transmission distance coefficient, which is marked as a.

[0045] It should be explained that if the number of data in the analysis data set is an odd number, the median of the analysis data set will be removed before screening.

[0046] The same operation is performed on the transmission volume data set. The filtered transmission volume coefficient is marked as b, the average of a and b is calculated and the calculation result is set as the error threshold. The system detects the current transmission data and calculates the transmission distance coefficient and transmission volume coefficient of the current transmission data. The average transmission distance coefficient and transmission volume coefficient of the current transmission data are calculated as the transmission data error rate.

[0047] When the error rate of the transmitted data exceeds the error threshold, the system determines that the current transmitted data is prone to errors and uses the cumulative sum check algorithm to make an initial judgment on the transmitted data. The specific steps of the cumulative sum check algorithm for error detection of the transmitted data are as follows:

[0048] Initialization: Set a cumulative sum variable and set it to 0;

[0049] Accumulate: accumulate the values ​​of all data bytes in the transmitted data into the accumulated sum variable;

[0050] Modulo: Perform a modulo operation on the accumulated sum variable to obtain the checksum, the modulus is usually 256;

[0051] Send: Send the checksum and transmission data to the receiver;

[0052] Receiving: The receiver receives the checksum and the transmitted data;

[0053] Checksum: The receiver performs the same accumulation operation on the transmitted data and obtains a checksum modulo the operation.

[0054] Comparison: Compare the received checksum with the calculated checksum. If the two are the same, the initial judgment passes; otherwise, the transmitted data is marked as erroneous data.

[0055] The system conducts initial error judgment on the transmitted data by evaluating the risk of errors in the transmitted data and using a simple accumulation and verification algorithm for the transmitted information with a high error rate, which greatly saves the computing space and cost of the verification data and improves the transmission efficiency.

[0056] It should be noted that, in the above accumulation process, the numerical value corresponding to the ASCII code of each data byte in the transmitted data is accumulated. The ASCII code is a character encoding standard used to represent characters as numbers so that computers can process and store information. For example, if the transmitted data is "Hello", the system will search for the ASCII codes of "H", "e", "l" and "o", which are 72, 101, 108 and 111 respectively. The accumulated sum variable is 0+72+101+108+108+111=500, which is taken modulo 256: 500%256=244, and the checksum is 244.

[0057] In step S3, when the transmission data is not marked as erroneous data after the initial judgment, the data source and data update frequency of the transmission data are collected. The more data sources of the transmission data and the faster the data update frequency, the more likely data duplication events will occur and the higher the data repetition rate. If explanation is required, the data repetition rate mentioned in this example means the probability of data duplication, not the degree of data duplication.

[0058] The data source can access the metadata field in the database table to obtain all data sources of the transmitted data and record the number of data sources of the transmitted data; the data update frequency can set a period of time as the analysis time, and record the number of supplementary transmissions of the transmitted data during the analysis time. The supplementary transmission data content is the updated or modified content of the transmitted data, and the number of supplementary transmissions can reflect the data update frequency.

[0059] Fuzzy reasoning is used to analyze the degree of data duplication and calculate the data duplication rate through data sources and data update frequency. The number of data sources and the number of supplementary transmission times are defined as input variables and divided into different fuzzy sets.

[0060] For example, "Many", "Few" for the number of data sources, "Big", "Small" for the number of supplementary transmissions.

[0061] The data duplication degree is defined as the output variable and divided into different fuzzy sets, for example, “High”, “Low” for the data duplication degree.

[0062] Formulate a set of fuzzy rules to describe the impact of different input variables on the output variables, such as:

[0063] The number of data sources is marked as S, the number of supplementary transmissions is marked as B, and the degree of data duplication is marked as C, then we can define

[0064] Ru l e1:IF(S is Many)AND(B is B ig)THEN(C is H i gh)

[0065] Ru l e1:IF(S is Few)AND(B is Sma ll)THEN(C is Low) ...

[0067] When the output result is "Low", it is judged that the data repetition degree is low, and the system provides an inverse code and an algorithm to detect the transmitted data; when the output result is "H i gh", it is judged that the data repetition degree is high, the system calculates the data repetition rate of the transmitted data and provides a BLAKE2 algorithm to detect the transmitted data.

[0068] The data repetition rate can be calculated using the exponential normalization formula: Where z is a normalization parameter, which can be obtained by summing the number of data sources and the number of supplementary transmissions of the transmitted data, F is the data repetition rate, and E is the natural base.

[0069] It should be noted that the division of fuzzy sets can be adjusted according to the actual accuracy required. For example, this example takes two fuzzy sets as an example. In fact, the number of data sources, the number of supplementary transmissions, and the degree of data duplication can also be divided into three or more sets to more accurately evaluate the degree of data duplication. In addition, for the number of data sources and the number of supplementary transmissions, thresholds can be set according to actual conditions for judgment. For example, when the number of data sources exceeds 10, it is marked as "Many", and when the number of supplementary transmissions exceeds 5, it is marked as "Big", etc., which will not be elaborated here.

[0070] In step S4, when the data duplication degree is low, the system uses a bitmap algorithm to detect the transmitted data. The specific steps are as follows:

[0071] Initialize the bitmap: create a bitmap array, which stores the index address of each character in the transmitted data.

[0072] Traverse the array: When the transmission data is transmitted, traverse the order and index address corresponding to each character in the transmission data; after receiving the transmission data, traverse the transmission data again and compare it with the bitmap array. When the index address corresponding to the character in the transmission data is the same as the index address of the corresponding character in the bitmap array, the corresponding character is judged to be repeated and a duplicate label is marked.

[0073] Output result: Set the comparison threshold, count the ratio of repeated character labels to the total characters of the transmitted data, and when the ratio exceeds the comparison threshold, set the output result to 1 for output; otherwise, set the output result to 0 for output.

[0074] When the output result is 1, the system sends a "data duplicate" prompt message to the user end, and when the output result is 0, the system sends a "verification passed" prompt message to the user end.

[0075] When the data duplication is high, the system uses the BLAKE2 algorithm to detect the transmitted data. The specific steps are as follows:

[0076] Initialization: define a 16-byte hash state tag as h;

[0077] Padding: Pad the transmitted data to make its length a multiple of 64 bytes; the padding method can add a byte 8 at the end of the data, and then add several zeros until the data length is a multiple of 64 bytes.

[0078] Compression: Divide the padded data into 64-byte blocks, each block as a group, use the G function to compress each group, mix the group data with the h state, and update the h state;

[0079] Output: After compressing all the groups, the h state contains the final hash value. The 16 bytes in the h state are output to obtain a 128-bit hash value.

[0080] The BLAKE2 algorithm is used to calculate the hash value when transmitting and interpreting the transmitted data. When the two calculated hash values ​​are the same, the system sends a "data duplication" prompt message to the user end. When the two calculated hash values ​​are different, the system sends a "verification passed" prompt message to the user end.

[0081] A mapping table is constructed based on the data repetition rate of the transmitted data and the hash value calculated by the BLAKE2 algorithm when it is transmitted. The calculated hash value is used as the key and the data repetition rate is used as the value and stored in a mapping table. When the transmitted data is received, its hash value is calculated again and the mapping table is queried. If the same hash value is found in the mapping table, it means that the data has appeared and the data repetition rate of the transmitted data can be obtained. If the same hash value is not found in the mapping table, the hash value and repetition rate of the transmitted data are recorded and added to the mapping table.

[0082] Selecting different algorithms to detect the transmitted data according to the degree of data duplication greatly improves the accuracy and efficiency of data duplication analysis. Constructing a mapping table to record and store the transmitted data facilitates the subsequent analysis and processing of the transmitted data.

[0083] It should be noted that the bitmap algorithm is a common data structure and algorithm, which is mainly used for efficient storage and processing of data. The bitmap algorithm is simple and efficient when analyzing data duplication; the BLAKE2 algorithm is a cryptographic hash algorithm, which is an improvement on the original BLAKE algorithm. The BLAKE2 algorithm has a large amount of calculation when detecting whether the transmitted data is repeated, but the detection accuracy is higher. When the BLAKE2 algorithm is filled, one character is regarded as a byte. For example, if the transmitted data is "He l lo", the system will fill the transmitted data with "He ll o80000...0" until the transmitted data is filled with a multiple of 64 bytes. The G function involved in the compression step above is a compression function, which can perform compression operations on data in different ways. Since the G function is a prior art means, it will not be analyzed here.

[0084] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0085] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application of the technical solution and the invention constraints. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0086] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0087] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0088] Finally: The above description is only 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 in the protection scope of the present invention.

Claims

1. A real-time multimedia message transmission method based on 5G network, characterized in that: The following steps are involved: Step S1: collecting transmission distances and transmission data volumes of multiple transmission channels for preprocessing; Step S2: setting an error threshold according to the pre-processed transmission distance and the amount of transmission data and calculating the transmission data error rate. When the transmission data error rate exceeds the error threshold, using the accumulation and verification algorithm to preliminarily determine whether the transmission is erroneous; Step S3: When it is preliminarily determined that the transmission is not wrong, the data source and update frequency of the transmission data are collected, and the data duplication degree is analyzed based on the data source and update frequency. If the data duplication degree is high, the data duplication rate is calculated; Step S4: Select a bitmap algorithm according to the degree of data duplication or apply the data repetition rate to the BLAKE 2 algorithm to detect whether the transmitted data has a data duplication problem.

2. A real-time multimedia message transmission method based on 5G network according to claim 1, characterized in that: In step S1, the transmission distance of the transmission channel cannot be directly obtained. The system calculates the physical distance between the two transmission devices and the network signal strength where the two transmission devices are located, and then performs a graded summation to obtain the calculated result. The transmission data volume of the transmission channel is obtained by detecting the size of the storage space occupied by the transmission data in the system.

3. A real-time multimedia message transmission method based on 5G network according to claim 2, characterized in that: In step S1, the system sets up multiple groups of transmission equipment, detects the transmission distance and transmission data volume of each group of transmission channels respectively, and performs normalization processing to obtain multiple groups of transmission distance coefficients and transmission volume coefficients.

4. A real-time multimedia message transmission method based on 5G network according to claim 3, characterized in that: In step S2, the processed transmission distance coefficients are combined into a transmission distance data set, and the transmission volume coefficients are combined into a transmission volume data set. The specific steps for setting the error threshold are as follows: The same processing is performed on the two data sets. The data set is used as the analysis data set. The analysis data set is divided into two parts of equal number. The average values ​​of the two data sets are calculated and compared respectively. The part with the larger average value is selected as the new round of analysis data set. The new round of analysis data set is then divided into two parts of equal number to calculate the average value. The part with the smaller average value is selected as the new round of analysis data set. The operation on the data set is repeated alternately by taking the larger and smaller values ​​until the last data is left. The average value of the data obtained after processing the two data sets is set as the error threshold.

5. A real-time multimedia message transmission method based on 5G network according to claim 4, characterized in that: In step S2, the system calculates the transmission distance coefficient and transmission volume coefficient of the transmission data to be tested and takes the average value as the transmission data error rate. When the transmission data error rate exceeds the error threshold, the system determines that the transmission data to be tested is prone to errors and uses the accumulation and verification algorithm to make an initial judgment on the transmission data.

6. A real-time multimedia message transmission method based on 5G network according to claim 1, characterized in that: In step S3, the data source obtains all data sources of the transmitted data by accessing the metadata field in the database table and records the number of data sources of the transmitted data; when obtaining the data update frequency, the number of supplementary transmissions of the transmitted data is recorded by setting a time period to reflect the data update frequency.

7. A real-time multimedia message transmission method based on 5G network according to claim 5, characterized in that: In step S3, the specific steps of using fuzzy reasoning to analyze the degree of data duplication are as follows: The number of data sources and the number of supplementary transmissions are defined as input variables and divided into fuzzy sets; The data duplication degree is defined as the output variable and divided into fuzzy sets; Formulate fuzzy rules to describe the impact of the number of data sources and the number of supplementary transmissions on the degree of data duplication; Perform fuzzy reasoning based on fuzzy rules to determine the degree of data duplication.

8. The real-time multimedia message transmission method based on 5G network according to claim 1, characterized in that: In step S3, when calculating the data repetition rate, the number of data sources of the transmitted data and the number of supplementary transmission times are summed to obtain a normalized parameter, and the normalized parameter is calculated using an exponential normalization formula.

9. A real-time multimedia message transmission method based on 5G network according to claim 8, characterized in that: In step S4, when the data duplication degree is low, the system uses the bitmap algorithm to detect the transmission data; when the data duplication degree is high, the system uses the BLAKE2 algorithm to detect the transmission data; If data duplication occurs in the transmitted data using the BLAKE2 algorithm, the data duplication rate of the transmitted data is given; if data duplication does not occur, the transmitted data is recorded.

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