Data processing system and method based on 5G wireless communication

Abstract

The invention discloses a data processing system and method based on 5G wireless communication, and relates to the technical field of data processing. According to the method, the roadside unit is matched through the mobile terminal, the data processing task is generated and sent to the roadside unit, whether the current computing resource of the cloud computing platform can be completed within the task ending completion time or not is judged, if not, processing is carried out on the roadside unit, and if yes, the data processing task is sent to the cloud computing platform. A data processing task information set is established according to historical data processing records, then a data processing task classification model is established, data processing tasks are classified, computing resources of a cloud computing platform are allocated through the data processing task information set, then multiple computing areas are divided, and corresponding data processing instructions are generated. Sending the data processing task to a corresponding calculation area according to a classification result of the data processing task, and executing the data processing task according to a data processing instruction of the calculation area; and intelligent classification processing of the data is realized.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and specifically to a 5G wireless communication data processing system and method. Background Art

[0002] With the advancement of technology, the fifth generation of mobile communications has gone from being highly anticipated to being within reach. Compared with the fourth generation of mobile communication networks, its high speed, large bandwidth, low latency, and massive connections can better serve various industrial chains. However, since the 5G network is currently in its early stages of construction, the scale of network sites is insufficient and the distribution is uneven, making it difficult for the 5G network to process data and respond as expected. With the continuous improvement and changes in people's living standards and daily needs, the Internet has become an indispensable part of people's daily lives, which has led to an increasing amount of data that needs to be processed in the network. With the continuous development of 5G technology, the data interaction rate has also increased. However, due to the current small number of 5G sites and the imperfect technology, the efficiency of data processing cannot meet expectations. However, most of the data processing problems on the Internet are not much different in essence. Therefore, most of the data processing problems can be solved by classifying each data processing problem and then finding a more unified data processing method. At the same time, the edge computing technology of 5G technology can be combined to improve the network response speed. To this end, a 5G wireless communication data processing system and method are provided. Summary of the invention

[0003] In order to solve the above technical problems, the object of the present invention is to provide a 5G wireless communication data processing system and method.

[0004] In order to achieve the above object, the present invention provides the following technical solutions: A 5G wireless communication data processing system includes a cloud computing platform, wherein the cloud computing platform is communicatively connected to a roadside unit management module, a task classification module, a computing resource allocation module, and a data processing module; The roadside unit management module is used to manage the roadside unit to receive data requests and generate data processing tasks, and it is provided with a data processing unit for localizing the data processing tasks; The task classification module is used to establish a data processing task classification model based on historical data processing records, extract data at the same time, and substitute the extracted data into the data processing task classification model to further classify the data processing tasks; The computing resource allocation module is used to allocate computing resources of the cloud computing platform according to the classification results of the data processing tasks, thereby establishing several computing areas and setting specific data processing instructions for each computing area; The data processing module is used to match the calculation area according to the classification result of the data processing task, execute the data processing task using the data processing instruction, and generate the historical data processing record.

[0005] Furthermore, the matching process between the roadside unit and the mobile terminal includes: The mobile terminal sends a data processing request to the cloud computing platform, and then the cloud computing platform obtains the location information of the mobile terminal according to the data processing request and sends it to the roadside unit management module; The roadside unit management module sets a number for each roadside unit. The roadside unit management module sends a signal response to the roadside unit closest to it and in an idle state according to the location information of the mobile terminal. The roadside unit matches the mobile terminal according to the signal response and sends a prompt to the mobile terminal that a data processing task can be submitted; The mobile terminal sends the data processing task to the roadside unit paired with it, where the data processing task includes the IP address of the mobile terminal, task data, and task deadline completion time.

[0006] Furthermore, the process of localizing the data processing task includes: After the roadside unit management module sends the computing task to the data processing module, if the roadside unit management module receives the local computing prompt and the data processing instruction returned by the data processing module, the roadside unit management module sends the data processing task and the data processing instruction to the data processing unit; The data processing unit determines whether a roadside unit can complete the data processing task within the task deadline, and sets one or more roadside units to perform the data processing task according to the judgment result, and sends the data processing result to the data processing module.

[0007] Furthermore, the classification process of the data processing task includes: The task classification module sets a number of data processing process extraction pointers, data content extraction pointers and data processing completion time extraction pointers, and then extracts data from each historical data processing record to obtain a number of data processing process extraction data, content extraction data, and data processing completion time. According to the data processing completion time, a number of data processing completion time intervals are established. At the same time, the same method for obtaining the data completion time interval is used to establish a number of data volume intervals. The task classification module establishes several data processing task information sets based on the extracted data, and then establishes a data processing task classification model, extracts data from the data processing task, and substitutes the extracted data into the data processing task classification model to classify it.

[0008] Furthermore, the computing resource allocation process includes: The computing resource allocation module first extracts data according to the data processing process in the data processing task information set to establish corresponding data processing instructions, sets several computing area labels according to the correspondence between the content extracted data and the data extracted by the data processing process, and divides the computing resources of the cloud computing platform into several sub-computing areas of the same size, integrates and divides the sub-computing areas according to the computing area labels, obtains multiple computing areas, and sets computing area labels for each computing area.

[0009] Furthermore, the execution process of the data processing task includes: According to the classification result of the data processing task, the task data contained therein is sent to the corresponding computing area, and then the computing area divides the task data into sub-task data of the same number as the sub-computing areas it contains, and each sub-task data is sent to the sub-computing area, and the first data processing is performed on each sub-task data according to the data processing instruction, and the processed sub-task data are integrated to obtain the first task result data. At the same time, the sub-task data is processed for the second time to obtain the second task result data, and the first task result data is compared with the second task result data to determine whether the two are consistent, and the data processing result is generated according to the determination result.

[0010] Furthermore, when the data processing module receives the data processing results and data processing tasks from the roadside unit management module, it executes the data processing tasks to obtain first task result data, and compares it with the data processing results from the roadside unit management module, and generates data processing results based on the judgment results and sends them to the roadside unit management module.

[0011] Furthermore, a data processing method based on a 5G wireless communication data processing system comprises the following steps: Step 1: Match the roadside unit through the mobile terminal, generate a data processing task and send it to the roadside unit; Step 2: determine whether the current computing resources of the cloud computing platform can complete the task within the deadline. If not, process it in the roadside unit. If yes, send the data processing task to the cloud computing platform. Step 3: Establish multiple data processing task information sets based on historical data processing records, then establish a data processing task classification model, and classify the data processing tasks; Step 4: Allocate computing resources of the cloud computing platform through the data processing task information set, divide into multiple computing areas, and generate corresponding data processing instructions; Step 5: Send the classification result of the data processing task to the corresponding computing area, and execute the data processing task according to the data processing instruction of the computing area.

[0012] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention matches and interacts with the data processing request end through the roadside unit, thereby generating data processing tasks. At the same time, if the computing resources of the cloud computing platform are insufficient, the data processing tasks can be processed locally through the roadside unit, which reduces the system computing amount of the cloud computing platform and improves the execution efficiency of the data processing tasks to a certain extent; 2. The present invention establishes a data processing task classification model through historical data processing records, and then classifies the data processing tasks, and divides the computing resources of the cloud computing platform into multiple computing areas according to the classification results of the data processing tasks, and sets corresponding data processing instructions for each computing area, and then processes the data processing tasks, thereby improving the accuracy of data processing to a certain extent. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] 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 will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0014] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0015] To make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described in detail below. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other implementation methods obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0016] like Figure 1 As shown, a 5G wireless communication data processing system includes a cloud computing platform, wherein the cloud computing platform includes a roadside unit management module, a task classification module, a computing resource allocation module and a data processing module; The roadside unit management module is used to manage the roadside unit to receive data requests from users, generate data processing tasks and send them to the task classification module and the data processing module, and manage the roadside unit to return the data processing results to the corresponding users; The roadside unit module is also provided with a data processing unit for localizing the data processing tasks; The specific process of the roadside unit management module managing the roadside unit is described below by way of an embodiment: The user sends a data processing request to the cloud computing platform through the mobile terminal, and then the cloud computing platform obtains the user's location information according to the data processing request and sends it to the roadside unit management module; The roadside unit management module sets a number for each roadside unit, for example, L 1 , L 2 ,……,L n , where n is a natural number greater than 0, and then the roadside unit management module sends a signal response to the roadside unit closest to the user and in an idle state according to the location information, and the roadside unit matches the user's mobile terminal according to the signal response, and sends a prompt to the user's mobile terminal that can submit a data processing task; The user sends the data processing task to the roadside unit paired with it through the mobile terminal, where the data processing task includes the IP address of the mobile terminal used by the user, the task data and the deadline for completion of the task; After receiving the data processing task, the roadside unit sends it to the task classification module and the data processing module; Further, after the roadside unit management module sends the computing task to the data processing module, if the local computing prompt and data processing instruction returned by the data processing module are received, the roadside unit management module sends the data processing task and the data processing instruction to the data processing unit; The data processing unit determines whether a roadside unit can complete the data processing task within the task deadline. If it is determined that the data processing task can be completed within the task deadline, the data processing unit sends the data processing task to the roadside unit matching the corresponding user mobile terminal, and the roadside completes the data processing task. If it is determined that the data processing task cannot be completed within the task deadline, the task data in the data processing task is divided into N sub-data of equal size, and the number of roadside units Num required to complete the corresponding data processing task is obtained according to the speed t of each roadside unit processing the sub-data and the task deadline T in the data processing task. The calculation formula is: ; The roadside unit management module selects a roadside unit that is in an idle state and has not been matched with a mobile terminal according to the required number of roadside units Num, changes its current state from an idle state to a task state, and sets the roadside unit matched with the mobile terminal corresponding to the data processing task as a temporary data processing center, and then each roadside unit processes the sub-data according to the data processing instruction and sends it to the temporary data processing center. When the roadside unit completes the assigned sub-data and sends it to the temporary data processing center, the roadside unit management module changes its state from a task state to an idle state; The temporary data processing center integrates all the sub-data processing results to obtain the data processing results and sends them to the data processing unit, and then the data processing unit sends the data processing results and the corresponding data processing tasks to the data processing module; Furthermore, after the roadside unit management module receives the data processing results of the data processing task from the data processing module, it sends the data processing results to the roadside unit paired with it according to the IP address of the mobile terminal in the data results, or when the correct prompt of the data processing results from the data processing module is received, the corresponding roadside unit sends the task processing results to the user's mobile terminal.

[0017] The task classification module is used to establish a data processing task classification model based on historical data processing records, extract data from the data processing tasks from the roadside unit management module, and substitute the extracted data into the data processing task classification model, thereby classifying the data processing tasks. The specific process includes: The task classification module sets a number of data processing process extraction pointers, data content extraction pointers and data processing completion time extraction pointers; Then the task classification module extracts data from each historical data processing record through the data processing process extraction pointer, data content extraction pointer and data processing completion time extraction pointer, obtains several data processing process extraction data, and sets the number C 1 , C 2 ,……,C a , get some content extraction data, and set the number X 1 , X 2 ,……,X b , get several data processing completion times, establish a rectangular coordinate system, and map all data processing completion times to the rectangular coordinate system, establish its corresponding normal distribution diagram, and then establish several data processing completion time intervals (0, Time 1 )、[Time 2 ,Time 3 ),……[Time k-1 ,Time k ], k is a natural number greater than 0, and the same method of obtaining data completion time is adopted to establish several data volume intervals (0, L 1 )、[L 2 ,L 3 ),……[L h-1 ,L h ], where h is a natural number greater than 0; It should be noted that the data processing process extracts data including the number of sub-computing areas called by the data processing module and the task data processed by it when processing the corresponding task data; The content extraction data includes a number of feature words and feature images. For example, the feature word may be car, the corresponding car name and model, star and the star name. The feature image is an image corresponding to the feature word. For example, if the feature word is car and the corresponding car name, the corresponding feature image is car. Furthermore, the task classification module establishes several data processing task information sets S according to the extracted data, sets the numbers and sends them to the computing resource allocation module, for example, S 1 , S 2 ,……,S j , where j is a natural number greater than 0; The data processing task information set S i ={C i，k , (X 1 , X 2 ,……,X k ), (Time p ,Time p+1 ), L q , L q+1 )}, C i，k Indicates the number is S i The data processing task information set includes a number C k Extract data from the data processing process; Then the task classification module integrates all data processing task information sets S to establish a data processing task classification model; Furthermore, when the task classification module receives the data processing task from the roadside unit management module, the task data in the data processing task is extracted through the data content extraction pointer, thereby obtaining a number of feature words and feature images, as well as the task data volume. At the same time, according to the task deadline completion time in the data processing task, the above data are substituted into the task data processing task model, thereby matching the corresponding data processing task information set S. The specific process includes: Find the data volume interval according to the task data volume in the data processing task, and then find the task deadline completion time interval according to the task deadline completion time in the data processing task; Then, the task classification module matches the corresponding data processing task information set S from the data processing task classification module according to the feature words, feature images, data volume area and task deadline extracted from the task data, and extracts the data processing process in the matched data processing task information set S and adds it to the data processing task, and then sends the data processing task to the data processing module.

[0018] The computing resource allocation module is used to allocate computing resources of the cloud computing platform according to the classification results of the data processing tasks, and send the allocation results to the data processing module. The specific process includes: The computing resource allocation module divides the computing resources of the cloud computing platform into a number of sub-computing areas of equal size and assigns a number to each sub-computing area; The computing resource allocation module receives the data processing task information set S from the task classification module, and then extracts data, data volume intervals, and corresponding feature words and feature data according to the data processing process in the data processing task information set S, and divides the sub-computing area into several computing areas, and the number of sub-computing areas contained in each computing area is not exactly the same; The specific process of integrating and dividing the sub-computing areas includes: The computing resource allocation module first extracts data from the data processing process in the data processing task information set S to establish a corresponding data processing instruction, and sets the same number as the corresponding data processing process extract data; The data processing instructions include a specific process of data processing, such as using keyword data cleaning in the process of data cleaning the task data, and whether to perform data mining, data reduction and data visualization operations on the task data after data cleaning; At the same time, the computing resource allocation module sets a number of computing area labels according to the correspondence between the content extraction data in the data processing task information set S and the data extraction data in the data processing process, wherein the computing area label includes a plurality of feature words, feature images, data processing instruction numbers and the number of sub-computing areas; Integrate and divide the sub-computation areas according to the calculation area labels to obtain multiple calculation areas, and set calculation area labels for each calculation area, and then the calculation resource allocation module sends the calculation area labels and data processing instructions to the data processing module; It should be noted that, in addition to dividing the computing resources of the cloud computing platform into sub-computing areas, the computing resource allocation module also divides the computing resources into temporary computing areas of the same size as the sub-computing areas but less in number than the sub-computing areas.

[0019] The data processing module is used to match the computing area according to the classification results of the data processing task, and use the dual computing mechanism and the corresponding data processing instructions to execute the data processing task, and generate historical data processing records and send them to the task classification module and the computing resource allocation module. The specific process includes: After receiving the data processing task from the task classification module, the data processing module matches the data number extracted from the data processing process in the data processing task with the computing resource area label from the computing resource allocation module to find the corresponding computing area; Then, the data processing module determines whether the number of sub-calculation areas in the corresponding calculation area can be completed within the task deadline. If it is determined that the task cannot be completed within the task deadline, the required number of temporary calculation areas are retrieved and temporarily incorporated into the corresponding calculation area. If the temporary calculation area is insufficient, the local calculation prompt and the corresponding data processing instruction are sent to the roadside unit management module. Further, the data processing module sends the tasks in the data processing task to the corresponding computing area, and then the computing area divides the task data into subtask data of the same number as the sub-computing areas and temporary computing areas it contains, and sends each subtask data to the sub-computing areas and temporary computing areas, and performs a first data processing on each subtask data according to the data processing instruction, and integrates the processed subtask data to obtain the first task result data; At the same time, after the first data processing is completed, the data processing module performs a second data processing on the subtask data, thereby obtaining the second task result data and comparing it with the first task result data. If the two are consistent, it is determined that the second task result data and the first task result are correct; If the two are inconsistent, the second task result data and the first task result are deleted, the sub-computation task is recalculated, and the two task result data are judged again to see if they are consistent. If they are still inconsistent, the first task result data shall prevail. Further, the data processing module generates a data processing result according to the first task result data and the data processing task and sends it to the roadside unit management module, and generates a historical data processing record and sends it to the task classification module, wherein the data processing result includes the first task result data and the IP address of the mobile terminal, and the historical data processing includes the task data, the data processing process, and the task execution time; It should be noted that when the data processing module receives the data processing results and data processing tasks from the roadside unit management module, the data processing module executes the data processing task to obtain the first task result data, and compares it with the data processing result from the roadside unit management module. If the two are consistent, a prompt indicating the correctness of the data processing result is sent to the roadside unit management module. If the two are inconsistent, a data processing result is generated based on the first task result data and the data processing task and sent to the roadside unit management module.

[0020] The present invention also discloses a data processing method based on a 5G wireless communication data processing system, comprising the following steps: Step 1: Match the roadside unit through the mobile terminal, generate a data processing task and send it to the roadside unit; Step 2: determine whether the current computing resources of the cloud computing platform can complete the task within the deadline. If not, process it in the roadside unit. If yes, send the data processing task to the cloud computing platform. Step 3: Establish multiple data processing task information sets based on historical data processing records, then establish a data processing task classification model, and classify the data processing tasks; Step 4: Allocate computing resources of the cloud computing platform through the data processing task information set, divide into multiple computing areas, and generate corresponding data processing instructions; Step 5: Send the classification result of the data processing task to the corresponding computing area, and execute the data processing task according to the data processing instruction of the computing area.

[0021] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A 5G wireless communication data processing system, including a cloud computing platform, characterized in that: The cloud computing platform is communicatively connected to a roadside unit management module, a task classification module, a computing resource allocation module, and a data processing module; The roadside unit management module is used to manage the roadside unit to receive data requests and generate data processing tasks, and it is provided with a data processing unit for localizing the data processing tasks; The task classification module is used to establish a data processing task classification model based on historical data processing records, extract data at the same time, and substitute the extracted data into the data processing task classification model to further classify the data processing tasks; The computing resource allocation module is used to allocate computing resources of the cloud computing platform according to the classification results of the data processing tasks, thereby establishing several computing areas and setting specific data processing instructions for each computing area; The data processing module is used to match the calculation area according to the classification result of the data processing task, execute the data processing task using the data processing instruction, and generate the historical data processing record.

2. A 5G wireless communication data processing system according to claim 1, characterized in that: The matching process between the roadside unit and the mobile terminal includes: The mobile terminal sends a data processing request to the cloud computing platform, and then the cloud computing platform obtains the location information of the mobile terminal according to the data processing request and sends it to the roadside unit management module; The roadside unit management module sets a number for each roadside unit. The roadside unit management module sends a signal response to the roadside unit closest to it and in an idle state according to the location information of the mobile terminal. The roadside unit matches the mobile terminal according to the signal response and sends a prompt to the mobile terminal that a data processing task can be submitted; The mobile terminal sends the data processing task to the roadside unit paired with it, where the data processing task includes the IP address of the mobile terminal, task data, and task deadline completion time.

3. A 5G wireless communication data processing system according to claim 1, characterized in that: The process of localizing the data processing task includes: After the roadside unit management module sends the computing task to the data processing module, if the roadside unit management module receives the local computing prompt and the data processing instruction returned by the data processing module, the roadside unit management module sends the data processing task and the data processing instruction to the data processing unit; The data processing unit determines whether a roadside unit can complete the data processing task within the task deadline, and sets one or more roadside units to perform the data processing task according to the judgment result, and sends the data processing result to the data processing module.

4. A 5G wireless communication data processing system according to claim 1, characterized in that: The classification process of the data processing tasks includes: The task classification module sets a number of data processing process extraction pointers, data content extraction pointers and data processing completion time extraction pointers, and then extracts data from each historical data processing record to obtain a number of data processing process extraction data, content extraction data, and data processing completion time. According to the data processing completion time, a number of data processing completion time intervals are established. At the same time, the same method for obtaining the data completion time interval is used to establish a number of data volume intervals. The task classification module establishes several data processing task information sets based on the extracted data, and then establishes a data processing task classification model, extracts data from the data processing task, and substitutes the extracted data into the data processing task classification model to classify it.

5. A 5G wireless communication data processing system according to claim 4, characterized in that: The computing resource allocation process includes: The computing resource allocation module first extracts data according to the data processing process in the data processing task information set to establish corresponding data processing instructions, sets several computing area labels according to the correspondence between the content extracted data and the data extracted by the data processing process, and divides the computing resources of the cloud computing platform into several sub-computing areas of the same size, integrates and divides the sub-computing areas according to the computing area labels, obtains multiple computing areas, and sets computing area labels for each computing area.

6. A 5G wireless communication data processing system according to claim 5, characterized in that: The execution process of the data processing task includes: According to the classification result of the data processing task, the task data contained therein is sent to the corresponding computing area, and then the computing area divides the task data into sub-task data of the same number as the sub-computing areas it contains, and each sub-task data is sent to the sub-computing area, and the first data processing is performed on each sub-task data according to the data processing instruction, and the processed sub-task data are integrated to obtain the first task result data. At the same time, the sub-task data is processed for the second time to obtain the second task result data, and the first task result data is compared with the second task result data to determine whether the two are consistent, and the data processing result is generated according to the determination result.

7. A 5G wireless communication data processing system according to claim 3, characterized in that: When the data processing module receives the data processing results and data processing tasks from the roadside unit management module, it executes the data processing tasks to obtain first task result data, and compares it with the data processing results from the roadside unit management module, and generates data processing results based on the judgment results and sends them to the roadside unit management module.

8. A data processing method based on a 5G wireless communication data processing system according to claims 1 to 7, characterized in that: The following steps are involved: Step 1: Match the roadside unit through the mobile terminal, generate a data processing task and send it to the roadside unit; Step 2: determine whether the current computing resources of the cloud computing platform can complete the task within the deadline. If not, process it in the roadside unit. If yes, send the data processing task to the cloud computing platform. Step 3: Establish multiple data processing task information sets based on historical data processing records, then establish a data processing task classification model, and classify the data processing tasks; Step 4: Allocate computing resources of the cloud computing platform through the data processing task information set, divide into multiple computing areas, and generate corresponding data processing instructions; Step 5: Send the classification result of the data processing task to the corresponding computing area, and execute the data processing task according to the data processing instruction of the computing area.

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