Data processing system for industrial network operation

Abstract

The invention discloses a data processing system for industrial network operation, which comprises a data acquisition module, a data processing module and a node management module, and is characterized in that the data acquisition module is used for acquiring service data in an industrial network and inputting the data into the system; the data processing module is used for clearing redundant and incomplete data in the data and guaranteeing that the processed data is correct, and the node management module is used for adjusting and distributing processing nodes and adjusting the load rate of the nodes for processing the data according to the capacity of the processed data. The data acquisition module, the data processing module and the node management module are electrically connected with one another, the data acquisition module comprises a monitoring module, a data collection module and a data entry module, and the monitoring module is used for monitoring data pulled in the system and data processed by a processing node. The method has the characteristics of improving the processing efficiency and improving the resource utilization rate.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a data processing system for industrial network operation. Background Art

[0002] With the rapid development of Internet technology, the number of factories using industrial Internet has increased rapidly, generating a large amount of data that needs to be processed and analyzed. The data generated by the system needs to be processed in a timely manner. At present, most industrial Internets include two parts: business system and analysis system. The business system is mainly responsible for processing the business data of the enterprise, and the analysis system is mainly responsible for analyzing the relevant data of the enterprise and extracting the value of the data. However, due to the different data formats in different application scenarios, the system is prone to data loading errors or data loss in the process of processing data. It is necessary to interrupt the data loading task and correct the erroneous data fragments. If there are multiple erroneous data, the correction node must be executed repeatedly each time, and the data correction order may be disordered. In the face of a large amount of data that needs to be corrected, the correction node will be congested, resulting in low system processing efficiency. Moreover, when processing data interaction of multiple clients, the existing technology is that the server processes based on the received client access request, distributes the data to the corresponding client, and renders the data on the client, and renders according to the number of client requests. The same data will be rendered multiple times in the same scenario, wasting a lot of computing resources and occupying a large number of data processing nodes. Therefore, it is very necessary to design a data processing system for industrial network operation that improves processing efficiency and resource utilization. Summary of the invention

[0003] The object of the present invention is to provide a data processing system for industrial network operation to solve the problems raised in the above background technology.

[0004] In order to solve the above technical problems, the present invention provides the following technical solutions: a data processing system for industrial network operation, comprising a data acquisition module, a data processing module and a node management module, characterized in that: the data acquisition module is used to collect business data in the industrial network and enter the data into the system, the data processing module is used to clear redundant and incomplete data in the data to ensure that the processed data is correct data, the node management module is used to adjust the allocation of processing nodes and adjust the load rate of the node processing data according to the processed data capacity, and the data acquisition module, the data processing module and the node management module are electrically connected to each other;

[0005] The node cluster management module includes a node adjustment submodule, a node replacement submodule and a thread management submodule. The node allocation submodule is used to allocate data correction nodes, the node replacement submodule is used to replace correction nodes that do not meet the conditions, and the thread management submodule is used to manage data correction threads.

[0006] According to the above technical solution, the data acquisition module includes a monitoring module, a data collection module and a data entry module. The monitoring module is used to monitor the data pulled from the system and the data processed by the processing node respectively. The data collection module is used to periodically pull system data through the industrial network port. The data entry module is used for operators to enter external data into the system.

[0007] According to the above technical solution, the data processing module includes a data preprocessing module, and the data preprocessing module is used to obtain data to eliminate redundant or incomplete data.

[0008] According to the above technical solution, the node management module includes a performance adjustment module and a node cluster management module, the node monitoring module is used to monitor the load rate of the processing node, and the node cluster management module is used to manage the processing node cluster.

[0009] According to the above technical solution, the data processing module also includes a data review module and a data correction module. The data review module is used to review whether errors occur in the transmitted data, and the data correction module is used to complete incomplete data and correct erroneous data.

[0010] According to the above technical solution, the operation method of the data processing system mainly includes the following steps:

[0011] Step S1: using the data collection module to periodically pull the operation data of the enterprise system through the enterprise system port, using the data entry module to enter the paper data, supplementary data and user access requests into the system, and using the monitoring module to monitor and retrieve the data before and after processing;

[0012] Step S2: When the network port is connected to retrieve or input data, the system sends an electrical signal to trigger the data protection module to start and start analyzing the data in the transmission line;

[0013] Step S3: When the data is inconsistent, the data correction module is started to analyze the specific location of the data error and replace the erroneous data;

[0014] Step S4: After the data is transmitted to the server, the system starts the data analysis module and starts analyzing the client's data request through the edge server;

[0015] Step S5: After anchoring the rendering data corresponding to the client request, the edge server builds a virtual transmission chain to connect the current client and the target client, and transmits the rendering data to the current client through the virtual transmission chain for response.

[0016] According to the above technical solution, step S2 further includes the following steps:

[0017] Step S21: call the target system data port, scan the data transmission protocol of the target system data port, identify the data type received by the transmission protocol, establish a transmission chain and connect with the data port according to the data type, and the system periodically pulls system data through the data port;

[0018] Step S22: Retrieve the data pulled through the data interface, the system scans and identifies the pulled data, eliminates redundant data in the pulled data, marks the incomplete data, retrieves the marked data and compares it with the original data in the target system collected by the monitoring module, if there is data similarity greater than a threshold under any attribute, then retrieve the original data with a similarity greater than the threshold, otherwise delete the current data;

[0019] Step S23: Retrieve the data in the target system collected by the monitoring module, and the system compares the data in the processing system with the data in the target system one by one. If there is a difference between the current data and the data in the target system, it means that there is an error in the current data, and the current data is marked as error data and the difference part is marked. If the data in the target system does not exist in the processing system, it means that the data in the processing system is missing, and the data is marked as missing data and the data location is marked.

[0020] According to the above technical solution, step S3 further includes the following steps:

[0021] Step S31: retrieve the operating status and data throughput speed of each processing node in the current node cluster, retrieve the amount of data to be corrected at the current marked position, and calculate the time required to correct the data according to the formula In the formula, i = 1, 2, 3...n, T represents the time required for the current correction node to correct the data, M represents the amount of data that needs to be corrected in the current area, represents the average data throughput speed of the current correction node, α represents the influence coefficient of the data transmission delay of the current correction node, sorts the time in ascending order, and marks the priority of the correction node according to the order from top to bottom;

[0022] Step S32: retrieve the time for each correction node to correct the data, and compare it with the time for the system to process the data. If there is a correction node among the current correction nodes whose correction data time is less than the system processing time, mark all correction nodes whose time is less than the system processing time, and sort them in ascending order. Select the correction node with the shortest time for processing. Otherwise, control the correction node to perform multi-threaded data correction.

[0023] According to the above technical solution, the step S32 further includes the following steps:

[0024] Step S321: retrieve the actual throughput and total throughput of the correction data of the current correction node, and calculate the efficiency of the current correction node through the formula In the formula, S represents the load efficiency of the current correction node, w represents the actual throughput of the current correction node, and W represents the total throughput of the current correction node. If the load efficiency of the current node is less than the threshold, it means that the correction node has entered the fatigue period, and the non-correction node is called to replace the current node. Otherwise, the current node continues to correct the data.

[0025] Step S322: When retrieving multi-threaded correction data, the system transfers the processing node to the backup database. The backup correction node divides and encapsulates the database according to the location of the data to be corrected. The backup correction node identifies missing or erroneous data in the blocked data block, retrieves the original data collected by the monitoring module to correct the erroneous data, retrieves the current modification thread, identifies the correction position of the current multi-threads, and compares the correction positions for overlap. If the data correction positions overlap, the overlapping threads will be merged. Otherwise, the system continues to lock and modify the resources.

[0026] According to the above technical solution, step S4 further includes the following steps:

[0027] Step S41: Retrieve the data request of the client, scan the data request, identify the data request feature, and retrieve the rendering data retained by the current client rendering node according to the data request feature. If the current client rendering node does not have the rendering data of the current request, anchor the rendering data retained by the client rendering node near the current client. Otherwise, directly retrieve the rendering data of the rendering node in the current client for response.

[0028] Step S42: Retrieve the location of the client that retains the rendering data, and calculate the distance between the current client and the client that retains the rendering data using the formula In the formula, (X 1 , Y 1 ) represents the current client location coordinates, (X 2 , Y 2) represents the location coordinates of the client that retains the rendering data. If the distance L is greater than the threshold set by the system, it means that the transmission time of the edge server retaining the rendering data is greater than the local rendering time, and local rendering is automatically performed. Otherwise, the retained rendering data is retrieved through the transmission node, and the request is responded to according to the retained rendering data.

[0029] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention can reduce the influence of redundant data on processing results and improve the accuracy of results by eliminating redundant data in the system; compare the data in the processing system with the data in the target system to complete the incomplete data; compare the data in the processing system with the data in the target system to quickly mark the location of the erroneous data, and then quickly correct it, further improving the speed of data processing; the time for each node to process the data in the current area can be quickly obtained through the above formula, and the best correction node can be further quickly allocated; by calculating the load efficiency of the current correction node and replacing the spare node when the load efficiency is less than the threshold, the best correction speed can be maintained at all times, the correction time can be reduced, and the efficiency of the system can be greatly improved; by dividing and encapsulating the database, the correction thread can accurately lock the position to be corrected when locking the resource area where the data to be corrected is located, preventing other threads from being unable to modify the data after the current modification thread locks the resource, further improving the efficiency of data correction; by calling the rendering data retained by the current client or the current client rendering node for response, the computing resources occupied by the repeated rendering of the data request at the current client rendering node can be reduced, the time required for rendering can be reduced, and the response efficiency of the system can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0031] Figure 1 It is a schematic diagram of the system module composition of the present invention. DETAILED DESCRIPTION

[0032] 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.

[0033] See also Figure 1The present invention provides a technical solution: a data processing system for industrial network operation, comprising a data acquisition module, a data processing module and a node management module, characterized in that: the data acquisition module is used to collect business data in the industrial network and enter the data into the system, the data processing module is used to clear redundant and incomplete data in the data to ensure that the processed data is correct data, the node management module is used to adjust the allocation of processing nodes and adjust the load rate of the node processing data according to the processed data capacity, and the data acquisition module, the data processing module and the node management module are electrically connected to each other;

[0034] The node cluster management module includes a node adjustment submodule, a node replacement submodule and a thread management submodule. The node allocation submodule is used to allocate data correction nodes, the node replacement submodule is used to replace correction nodes that do not meet the conditions, and the thread management submodule is used to manage data correction threads.

[0035] The data acquisition module includes a monitoring module, a data collection module and a data entry module. The monitoring module is used to monitor the data pulled from the system and the data processed by the processing node respectively. The data collection module is used to periodically pull system data through the industrial network port. The data entry module is used for operators to enter external data into the system.

[0036] The data processing module includes a data preprocessing module, which is used to obtain data and eliminate redundant or incomplete data in the data.

[0037] The node management module includes a performance adjustment module and a node cluster management module. The node monitoring module is used to monitor the load rate of the processing node, and the node cluster management module is used to manage the processing node cluster.

[0038] The data processing module also includes a data review module and a data correction module. The data review module is used to review whether there are errors in the transmitted data, and the data correction module is used to complete the incomplete data and correct the erroneous data.

[0039] The operation method of the data processing system mainly includes the following steps:

[0040] Step S1: using the data collection module to periodically pull the operation data of the enterprise system through the enterprise system port, using the data entry module to enter the paper data, supplementary data and user access requests into the system, and using the monitoring module to monitor and retrieve the data before and after processing;

[0041] Step S2: When the network port is connected to retrieve or input data, the system sends an electrical signal to trigger the data protection module to start and start analyzing the data in the transmission line;

[0042] Step S3: When the data is inconsistent, the data correction module is started to analyze the specific location of the data error and replace the erroneous data;

[0043] Step S4: After the data is transmitted to the server, the system starts the data analysis module and starts analyzing the client's data request through the edge server;

[0044] Step S5: After anchoring the rendering data corresponding to the client request, the edge server builds a virtual transmission chain to connect the current client and the target client, and transmits the rendering data to the current client through the virtual transmission chain for response.

[0045] Step S2 further comprises the following steps:

[0046] Step S21: call the target system data port, scan the data transmission protocol of the target system data port, identify the data type received by the transmission protocol, establish a transmission chain and connect with the data port according to the data type, and the system periodically pulls system data through the data port;

[0047] Step S22: Retrieve the data pulled through the data interface, the system scans and identifies the pulled data, eliminates redundant data in the pulled data, and marks the incomplete data, retrieves the marked data and compares it with the original data in the target system collected by the monitoring module. If there is data similarity under any attribute greater than the threshold, it means that the currently marked missing data exists in the original data, and the original data with similarity greater than the threshold is retrieved. Otherwise, the current data is deleted. By eliminating redundant data in the system, the influence of redundant data on the processing results can be reduced, and the accuracy of the results can be improved. By comparing the data in the processing system with the data in the target system, the incomplete data can be completed.

[0048] Step S23: Retrieve the data in the target system collected by the monitoring module, and the system compares the data in the processing system with the data in the target system one by one. If there is a difference between the current data and the data in the target system, it means that there is an error in the current data, and the current data is marked as erroneous data and the difference is marked. If the data in the target system does not exist in the processing system, it means that the data in the processing system is missing, and the data is marked as missing data and the data location is marked. By comparing the data in the processing system with the data in the target system, the location of the erroneous data can be quickly marked and then quickly corrected, further improving the speed of data processing.

[0049] Step S3 further comprises the following steps:

[0050] Step S31: retrieve the operating status and data throughput speed of each processing node in the current node cluster, retrieve the amount of data to be corrected at the current marked position, and calculate the time required to correct the data according to the formula In the formula, i = 1, 2, 3...n, T represents the time required for the current correction node to correct the data, M represents the amount of data that needs to be corrected in the current area, represents the average data throughput speed of the current correction node, α represents the influence coefficient of the data transmission delay of the current correction node, sorts the time in ascending order, and marks the priority of the correction node according to the order from top to bottom. The above formula can quickly obtain the time for each node to process the current area data, and further quickly allocate the best correction node;

[0051] Step S32: retrieve the time for each correction node to correct the data, and compare it with the time for the system to process the data. If there is a correction node among the current correction nodes whose correction time is less than the system processing time, it means that the current correction node can correct the data within the time for the system to process the data. Mark all correction nodes whose time is less than the system processing time, and sort them in ascending order. Select the correction node with the shortest time for processing. Otherwise, it means that data congestion will occur in the process of the correction node correcting the data, and control the correction node to perform multi-threaded data correction.

[0052] Step S32 further includes the following steps:

[0053] Step S321: retrieve the actual throughput and total throughput of the correction data of the current correction node, and calculate the efficiency of the current correction node through the formula In the formula, S represents the load efficiency of the current correction node, w represents the actual throughput of the current correction node, and W represents the total throughput of the current correction node. If the load efficiency of the current node is less than the threshold, it means that the correction node has entered the fatigue period, and the non-correction node is called to replace the current node. Otherwise, the current node continues to correct the data. By calculating the load efficiency of the current correction node and replacing the standby node when the load efficiency is less than the threshold, the optimal correction speed can be maintained at all times, the correction time can be reduced, and the efficiency of the system can be greatly improved.

[0054] Step S322: When retrieving multi-threaded correction data, the system transfers the processing node to the backup database. The backup correction node divides the database according to the location of the data to be corrected and encapsulates it. The backup correction node identifies missing or erroneous data in the blocked data block, retrieves the original data collected by the monitoring module to correct the erroneous data, calls the current modification thread, identifies the correction position of the current multi-threads, and compares the correction positions for overlap. If the data correction positions overlap, it means that one of the threads will lock the resources during the modification process, and the other threads will wait for resources, causing thread congestion. The overlapping threads will be merged, otherwise the system will continue to perform resource lock modification. By dividing and encapsulating the database, the correction thread can accurately lock the position to be corrected when locking the resource area where the data to be corrected is located, preventing other threads from being able to modify the data after the current modification thread locks the resources, thereby further improving the efficiency of data correction.

[0055] Step S4 further comprises the following steps:

[0056] Step S41: Retrieve the data request of the client, scan the data request, identify the data request feature, and retrieve the rendering data retained by the current client rendering node according to the data request feature. If the current client rendering node does not have the rendering data of the current request, anchor the rendering data retained by the client rendering node near the current client. Otherwise, directly retrieve the rendering data of the rendering node in the current client for response. By retrieving the rendering data retained by the current client or the current client rendering node for response, the computing resources occupied by the repeated rendering of the data request in the current client rendering node can be reduced, the time required for rendering can be reduced, and the response efficiency of the system can be improved.

[0057] Step S42: Retrieve the location of the client that retains the rendering data, and calculate the distance between the current client and the client that retains the rendering data using the formula In the formula, (X 1 , Y 1 ) represents the current client location coordinates, (X 2 , Y 2 ) represents the location coordinates of the client that retains the rendering data. If the distance L is greater than the threshold set by the system, it means that the transmission time of the edge server retaining the rendering data is greater than the local rendering time, and local rendering is automatically performed. Otherwise, the reserved rendering data is retrieved through the transmission node, and the request is responded to according to the reserved rendering data. By calculating the distance between the two client rendering nodes, the server with the rendering data retained with a short transmission distance and a short time can be quickly selected.

[0058] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0059] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A data processing system for industrial network operation, comprising a data acquisition module, a data processing module and a node management module, characterized in that: The data acquisition module is used to collect business data in the industrial network and enter the data into the system. The data processing module is used to remove redundant and incomplete data in the data to ensure that the processed data is correct. The node management module is used to adjust the allocation of processing nodes and adjust the load rate of the node processing data according to the processed data capacity. The data acquisition module, the data processing module and the node management module are electrically connected to each other; The node cluster management module includes a node adjustment submodule, a node replacement submodule and a thread management submodule. The node allocation submodule is used to allocate data correction nodes, the node replacement submodule is used to replace correction nodes that do not meet the conditions, and the thread management submodule is used to manage data correction threads.

2. A data processing system for industrial network operation according to claim 1, characterized in that: The data acquisition module includes a monitoring module, a data collection module and a data entry module. The monitoring module is used to monitor the data pulled from the system and the data processed by the processing node respectively. The data collection module is used to periodically pull system data through the industrial network port. The data entry module is used for operators to enter external data into the system.

3. A data processing system for industrial network operation according to claim 2, characterized in that: The data processing module includes a data preprocessing module, and the data preprocessing module is used to obtain data and eliminate redundant or incomplete data in the data.

4. A data processing system for industrial network operation according to claim 3, characterized in that: The node management module includes a performance adjustment module and a node cluster management module. The node monitoring module is used to monitor the load rate of the processing node, and the node cluster management module is used to manage the processing node cluster.

5. A data processing system for industrial network operation according to claim 4, characterized in that: The data processing module also includes a data review module and a data correction module. The data review module is used to review whether errors occur in the transmitted data, and the data correction module is used to complete incomplete data and correct erroneous data.

6. A data processing system for industrial network operation according to claim 5, characterized in that: The operation method of the data processing system mainly comprises the following steps: Step S1: using the data collection module to periodically pull the operation data of the enterprise system through the enterprise system port, using the data entry module to enter the paper data, supplementary data and user access requests into the system, and using the monitoring module to monitor and retrieve the data before and after processing; Step S2: When the network port is connected to retrieve or input data, the system sends an electrical signal to trigger the data protection module to start and start analyzing the data in the transmission line; Step S3: When the data is inconsistent, the data correction module is started to analyze the specific location of the data error and replace the erroneous data; Step S4: After the data is transmitted to the server, the system starts the data analysis module and starts analyzing the client's data request through the edge server; Step S5: After anchoring the rendering data corresponding to the client request, the edge server builds a virtual transmission chain to connect the current client and the target client, and transmits the rendering data to the current client through the virtual transmission chain for response.

7. A data processing system for industrial network operation according to claim 6, characterized in that: The step S2 further comprises the following steps: Step S21: call the target system data port, scan the data transmission protocol of the target system data port, identify the data type received by the transmission protocol, establish a transmission chain and connect with the data port according to the data type, and the system periodically pulls system data through the data port; Step S22: Retrieve the data pulled through the data interface, the system scans and identifies the pulled data, eliminates redundant data in the pulled data, marks the incomplete data, retrieves the marked data and compares it with the original data in the target system collected by the monitoring module, if there is data similarity greater than a threshold under any attribute, then retrieve the original data with a similarity greater than the threshold, otherwise delete the current data; Step S23: Retrieve the data in the target system collected by the monitoring module, and the system compares the data in the processing system with the data in the target system one by one. If there is a difference between the current data and the data in the target system, it means that there is an error in the current data, and the current data is marked as error data and the difference part is marked. If the data in the target system does not exist in the processing system, it means that the data in the processing system is missing, and the data is marked as missing data and the data location is marked.

8. A data processing system for industrial network operation according to claim 7, characterized in that: The step S3 further comprises the following steps: Step S31: retrieve the operating status and data throughput speed of each processing node in the current node cluster, retrieve the amount of data to be corrected at the current marked position, and calculate the time required to correct the data according to the formula In the formula, i = 1, 2, 3...n, T represents the time required for the current correction node to correct the data, M represents the amount of data that needs to be corrected in the current area, represents the average data throughput speed of the current correction node, α represents the influence coefficient of the data transmission delay of the current correction node, sorts the time in ascending order, and marks the priority of the correction node according to the order from top to bottom; Step S32: retrieve the time for each correction node to correct the data, and compare it with the time for the system to process the data. If there is a correction node among the current correction nodes whose correction data time is less than the system processing time, mark all correction nodes whose time is less than the system processing time, and sort them in ascending order. Select the correction node with the shortest time for processing. Otherwise, control the correction node to perform multi-threaded data correction.

9. A data processing system for industrial network operation according to claim 8, characterized in that: The step S32 further comprises the following steps: Step S321: retrieve the actual throughput and total throughput of the correction data of the current correction node, and calculate the efficiency of the current correction node through the formula In the formula, S represents the load efficiency of the current correction node, w represents the actual throughput of the current correction node, and W represents the total throughput of the current correction node. If the load efficiency of the current node is less than the threshold, it means that the correction node has entered the fatigue period, and the non-correction node is called to replace the current node. Otherwise, the current node continues to correct the data. Step S322: When retrieving multi-threaded correction data, the system transfers the processing node to the backup database. The backup correction node divides and encapsulates the database according to the location of the data to be corrected. The backup correction node identifies missing or erroneous data in the blocked data block, retrieves the original data collected by the monitoring module to correct the erroneous data, retrieves the current modification thread, identifies the correction position of the current multi-threads, and compares the correction positions for overlap. If the data correction positions overlap, the overlapping threads will be merged. Otherwise, the system continues to lock and modify the resources.

10. A data processing system for industrial network operation according to claim 9, characterized in that: The step S4 further comprises the following steps: Step S41: Retrieve the data request of the client, scan the data request, identify the data request feature, and retrieve the rendering data retained by the current client rendering node according to the data request feature. If the current client rendering node does not have the rendering data of the current request, anchor the rendering data retained by the client rendering node near the current client. Otherwise, directly retrieve the rendering data of the rendering node in the current client for response. Step S42: Retrieve the location of the client that retains the rendering data, and calculate the distance between the current client and the client that retains the rendering data using the formula Wherein, (X1, Y1) represents the location coordinates of the current client, (X2, Y2) represents the location coordinates of the client that retains the rendering data. If the distance L is greater than the threshold set by the system, it means that the transmission time of the edge server retaining the rendering data is greater than the local rendering time, and local rendering is automatically performed. Otherwise, the reserved rendering data is retrieved through the transmission node, and the request is responded to according to the reserved rendering data.

Images