Data processing method and device and data generation method

Abstract

The embodiment of the invention discloses a data processing method and device and a data generation method, and the method comprises the steps: obtaining a plurality of pieces of network transmission data with the same task identifier; the network transmission data is generated based on a data transmission rule; the data transmission rule at least comprises a device identifier, a task identifier and a communication service identifier; dividing the plurality of pieces of network transmission data based on the device identifier corresponding to each piece of network transmission data and the plurality of communication service identifiers corresponding to each piece of network device, and determining a plurality of data subsets; for each data subset, generating a set identifier of the data subset based on the device identifier and the communication service identifier of the data subset; and determining the network data file under the same task identifier based on all the data subsets under the same task identifier and the set identifiers corresponding to all the data subsets.

Description

Technical Field

[0001] The present application relates to but is not limited to the field of communication technology, and in particular to a data processing method, device, and data generation method. Background Art

[0002] In existing scenarios, in order to analyze the operating status of a communication base station, it is usually necessary to obtain network data collected by the network equipment under the communication base station, so that a corresponding network data file can be generated based on the network data, and the operating status of the communication base station can be analyzed through the network data file. However, with the development of multi-task scenarios of communication base stations, there is currently no better method to process the network data in multi-task scenarios to generate network data files. Summary of the invention

[0003] In view of this, embodiments of the present application at least provide a data processing method, device, and data generating method.

[0004] The technical solution of the embodiment of the present application is implemented as follows:

[0005] On the one hand, an embodiment of the present application provides a data processing method, the method comprising:

[0006] Acquire multiple network transmission data with the same task identifier; the network transmission data is generated based on a data transmission rule; the data transmission rule includes at least a device identifier, a task identifier and a communication service identifier;

[0007] Based on the device identifiers corresponding to each piece of network transmission data and the multiple communication service identifiers corresponding to each network device, the multiple pieces of network transmission data are divided to determine multiple data subsets;

[0008] For each data subset, generating a collection identifier of the data subset based on the device identifier and the communication service identifier of the data subset;

[0009] Based on all data subsets under the same task identifier and the set identifiers corresponding to all data subsets, the network data files under the same task identifier are determined.

[0010] On the other hand, an embodiment of the present application provides a data processing device, the device comprising:

[0011] The data collection module, the data processing module and the file generation module are connected in sequence; wherein,

[0012] A data collection module, configured to receive a plurality of network transmission data respectively sent by a plurality of network devices in response to the triggering of a network monitoring task; the network transmission data is generated based on a data transmission rule; the data transmission rule at least includes a device identifier, a task identifier and a communication service identifier;

[0013] The data processing module is used to obtain multiple network transmission data with the same task identifier; divide the multiple network transmission data based on the device identifier corresponding to each network transmission data and the multiple communication service identifiers corresponding to each network device to determine multiple data subsets; for each data subset, generate a collection identifier of the data subset based on the device identifier and the communication service identifier of the data subset;

[0014] The file generation module is used to determine the network data file under the same task identification based on all the data subsets under the same task identification and the set identifications corresponding to all the data subsets.

[0015] On the other hand, the embodiment of the present application provides a data generation method, the method comprising:

[0016] In response to the triggering of the network monitoring task, a plurality of network data under a plurality of communication services collected by the network device are obtained;

[0017] Encapsulate multiple network data respectively based on data transmission rules to generate multiple network transmission data;

[0018] The plurality of network transmission data are sent to the data processing device.

[0019] It should be understood that the above general description and the following detailed description are merely exemplary and explanatory, and are not intended to limit the technical solutions of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The drawings herein are incorporated into the specification and constitute a part of the specification. These drawings illustrate embodiments consistent with the present application and are used together with the specification to illustrate the technical solution of the present application.

[0021] Figure 1 A schematic diagram of an implementation process of a data processing method provided in an embodiment of the present application Figure 1 ;

[0022] Figure 2 A schematic diagram of an implementation process of a data processing method provided in an embodiment of the present application Figure 2 ;

[0023] Figure 3 A schematic diagram of network transmission data in a multi-tasking scenario provided by an embodiment of the present application;

[0024] Figure 4A schematic diagram of a method for generating a network data file provided in an embodiment of the present application;

[0025] Figure 5 A schematic diagram of an implementation flow of a data generation method provided in an embodiment of the present application;

[0026] Figure 6 A schematic diagram of a data processing device provided in an embodiment of the present application;

[0027] Figure 7 A schematic diagram of a key business data processing device provided in an embodiment of the present application Figure 1 ;

[0028] Figure 8 A schematic diagram of a key business data processing device provided in an embodiment of the present application Figure 2 ;

[0029] Fig. 9 A schematic diagram of an implementation process of a data processing method provided in an embodiment of the present application Figure 3 ;

[0030] Fig.10 A schematic diagram of an application scenario of a data processing method provided in an embodiment of the present application;

[0031] Fig.11 A hardware entity diagram of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0032] In order to make the purpose, technical solutions and advantages of the present application clearer, the technical solutions of the present application are further elaborated in detail below in conjunction with the drawings and embodiments. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0033] In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0034] The present application embodiment provides a data processing method, such as Figure 1 As shown, it may include steps S101 to S104:

[0035] Step S101: Acquire multiple network transmission data with the same task identifier.

[0036] Wherein, the network transmission data is generated based on the data transmission rules; the data transmission rules at least include the device identification, the task identification and the communication service identification;

[0037] Here, multiple network transmission data refers to at least two network transmission data. Task identifier refers to an identifier named for a task, which is used to distinguish and identify different tasks. For example, a task identifier can be a network monitoring task generated based on a performance report or a measurement report. Device identifier refers to an identifier named for a device, which is used to distinguish and identify different devices. For example, a device identifier can be a network element ID (Identity). Communication service identifier refers to an identifier named for a communication service, which is used to distinguish and identify different communication services. For example, a communication service identifier can be a PLMN (Public Land Mobile Network) ID.

[0038] The data transmission rules include at least a device identifier, a task identifier and a communication service identifier. It can be understood that the data transmission rules include at least fields for representing the device identifier, the task identifier and the communication service identifier. In this way, the network transmission data generated based on the data transmission rules includes the task identification information of the task corresponding to the network transmission data, the device identification information of the network device that generates the network transmission data, and the communication service identification information corresponding to the network transmission data.

[0039] In some implementations, each piece of network transmission data includes at least a device identifier, a task identifier, and a communication service identifier, so that multiple pieces of network transmission data with the same task identifier can be determined based on the task identifier in each piece of network transmission data received.

[0040] In some embodiments, after obtaining multiple network transmission data with the same task identifier, the multiple network transmission data with the same task identifier can be stored in different storage areas in the data processing device, where the storage area can be a cache area and / or a data table. In this way, when processing multiple network transmission data with the same task identifier, the storage area under the corresponding task identifier can be used to obtain the multiple network transmission data with the task identifier.

[0041] Step S102: based on the device identifiers corresponding to each piece of network transmission data and the multiple communication service identifiers corresponding to each network device, the multiple pieces of network transmission data are divided to determine multiple data subsets;

[0042] Here, the multiple data subsets refer to at least two data subsets, and each data subset includes at least one network transmission data.

[0043] In some embodiments, each network transmission data includes at least a device identifier, a task identifier, and a communication service identifier. In this way, multiple network transmission data with the same task identifier can be divided according to the device identifier in the network transmission data to obtain multiple network transmission data under the same device identifier, and then the multiple network transmission data under the same device identifier can be divided according to the communication service identifier in the network transmission data to obtain multiple data subsets.

[0044] For example, a method for processing network transmission data sent by a network device in a distributed unit (DU)-centralized unit (CU) separation scenario is described, such as Figure 2 As shown, it can be seen that DU network elements and CU network elements from different suppliers send multiple network transmission data to the data processing device, and the multiple network transmission data sent by different network elements include network transmission data based on different tasks, wherein the network transmission data under the same task corresponds to network transmission data under different communication services. In this way, the data processing module in the data processing device can process the received network transmission data according to the anchor mark in the network transmission data, namely the task ID, network element ID and PLMN ID. During implementation, the network transmission data with the same task ID is divided according to the secondary anchor 22, namely the network element ID, and the tertiary anchor 23, namely the PLMN ID. For example, for multiple network data with the task ID TASK_NUM-N, firstly, four sets are divided based on the network element ID, and the network element IDs corresponding to the four sets are CU-1, CU-2, DU-1, and DU-2, respectively, and then the network transmission data under each set is divided according to the PLMN ID.

[0045] It can be understood that the device identifier, communication service identifier and task identifier in each piece of network transmission data in each data subset are the same.

[0046] Step S103: for each data subset, based on the device identifier and the communication service identifier of the data subset, generate a collection identifier of the data subset;

[0047] Here, the set identifier refers to an identifier for naming a data subset, which is used to distinguish and identify different data subsets. For example, the set identifier can be generated based on the business data representation (Logical Device Number, LDN) method.

[0048] It is understandable that the device identifier and communication service identifier of each network transmission data in the data subset are the same, so that the set identifier generated based on the device identifier and communication service identifier of the data subset can uniquely identify the corresponding data subset.

[0049] For example, Figure 2 As shown, in the data processing module, after dividing multiple network transmission data with the same task ID according to the secondary anchor point 22, i.e., the network element ID, and the tertiary anchor point 23, i.e., the PLMN ID, the association of the network transmission data with the same PLMN ID and the same task ID reported by the CU network element and the DU network element is completed, and the corresponding set identifier, i.e., the LDN data 24, is generated based on the network element ID and the PLMN ID in the associated network transmission data.

[0050] Step S104: Based on all the data subsets under the same task identifier and the set identifiers corresponding to all the data subsets, determine the network data files under the same task identifier.

[0051] In some implementations, the set identifiers corresponding to all data subsets under the same task identifier are mapped and stored, so that the network data file under the same task identifier can be obtained.

[0052] For example, a data processing method for network transmission data in a DU-CU separation scenario is described, such as Figure 2 As shown, after the LDN data 24 is generated, the data subset is associated with the corresponding LDN data 24, and a network data file under the same task ID is generated. For example, the network data file generated for the task ID TASK_NUM-N is the TASK2 performance file 26.

[0053] In the embodiment of the present application, firstly, through the task identifier in the network transmission data, the first division of multiple network transmission data reported by multiple network devices can be realized, so that multiple network transmission data with the same task identifier can be obtained, and then the multiple network transmission data with the same task identifier are divided according to the device identifier and the communication service identifier to obtain multiple data subsets, so that the device identifier, communication service identifier and task identifier in the network transmission data in each data subset are the same, so that the set identifier associated with the data subset can be generated based on the device identifier, communication service identifier and task identifier in each data subset, and finally the set identifier and the data subset are stored correspondingly. The data processing method processes the network transmission data reported by multiple different network devices in a hierarchical manner, so that the data in the obtained network data file has a regularity, so that the network transmission data file is applied in the subsequent analysis process of the communication base station, and the corresponding network transmission data can be found according to the set identifier required for the analysis, which not only improves the speed of the analysis of the network transmission data, but also solves the problem of chaotic collection of network transmission data in multi-task scenarios, improves the accuracy of the generated network data file, and thus improves the accuracy of the analysis result based on the network data file.

[0054] In some embodiments, the above step S101, obtaining multiple network transmission data with the same task identifier, may include step S1011 and step S1012:

[0055] Step S1011: in response to the triggering of the network monitoring task, receiving a plurality of network transmission data respectively sent by a plurality of network devices;

[0056] Here, the network device refers to a hardware device used to establish, manage and maintain a communication network. For example, the network device may be a network element device. The plurality of network devices may be at least two network devices.

[0057] In some embodiments, in response to the triggering of a network monitoring task, the network monitoring task can be divided into a plurality of network monitoring subtasks and sent to the corresponding network device, so that after receiving the network monitoring subtask, the network device executes the corresponding network monitoring subtask, determines the corresponding network transmission data based on the network monitoring subtask, and sends it to the data processing device. Each network monitoring subtask corresponds to a task identifier.

[0058] In some embodiments, the network monitoring task may be a performance monitoring task or a measurement reporting task, wherein when the network monitoring task is implemented as a performance monitoring task, the network transmission data may be performance management (Performance Management, PM) data, and when the network monitoring task is implemented as a measurement reporting task, the network transmission data may be measurement report (Measurement Report, MR) data.

[0059] In some embodiments, the multiple network devices may be devices from different vendors and / or network devices of different types, where devices from different vendors refer to network devices having different device source information, and different types of network devices may be DU network element devices and CU network element devices.

[0060] For example, the network transmission data in the DU-CU separation scenario is described, such as Figure 3 As shown, each network element device comes from a different supplier, for example, DU network element 31 from supplier A, DU network element 32 from supplier B, CUUP network element 33 from supplier C and CUUP network element 34 from supplier D. The DU network element 31 from supplier A is used for illustration. Based on the network monitoring task, two network monitoring subtasks (for example, TASK1 and TASK2) are decomposed under the network element, wherein the tasks under TASK1 include multiple different communication services, for example, communication services including PLMN3, PLMN4, etc.

[0061] Step S1012: Based on the task identifier corresponding to each piece of network transmission data, multiple pieces of network transmission data respectively sent by multiple network devices are divided to determine multiple pieces of network transmission data respectively corresponding to at least one task identifier.

[0062] In some implementations, multiple network transmission data sent by the received network device are divided according to the task identifier, and multiple network transmission data under the same task identifier are obtained respectively, so that multiple network transmission data corresponding to at least one task identifier can be obtained based on the received network transmission data.

[0063] For example, a data processing method is described for network transmission data in a DU-CU separation scenario, such as Figure 2 As shown, in the data processing module, the network transmission data is divided according to the first-level anchor point 21, namely the task ID, and can be divided into two first-level anchor points 21, namely, multiple network transmission data corresponding to the task ID TASK_NUM-N and multiple network transmission data corresponding to the task ID TASK_NUM-NE.

[0064] In the above embodiment, multiple network transmission data reported by the network device can be initially divided based on the task identifier to obtain multiple network transmission data under each task identifier in the multi-task scenario, so that the multiple network transmission data under the same task identifier can be subsequently divided based on the device identifier and the communication service identifier.

[0065] In some embodiments, after the above step S104, steps S105 and S106 may be included:

[0066] Step S105: Obtaining network data files corresponding to all task identifiers;

[0067] In some implementations, network data files respectively corresponding to a plurality of network monitoring subtasks corresponding to the network monitoring task may be obtained.

[0068] For example, a data processing method is described for network transmission data in a DU-CU separation scenario, such as Figure 2 As shown, the network monitoring task is divided into two network monitoring sub-tasks. According to the multiple network transmission data sent to the data processing device by DU network elements and CU network elements from different suppliers, the multiple network transmission data are first divided according to the first-level anchor point 21, that is, the task ID. It can be seen that two first-level anchor points 21 are divided, that is, the task IDs are TASK_NUM-N and TASK_NUM-NE respectively. The network data file obtained for TASK_NUM-N is the TASK2 performance file 26, and the network data file obtained for TASK_NUM-NE is the TASK1 performance file 25.

[0069] Step S106: Generate a network monitoring file for the network monitoring task based on all network data files.

[0070] In some implementations, the data subsets in each network data file can be integrated, and the collection identifiers in each network data file can be correspondingly integrated, so that a first file based on the data subsets and a second file based on the collection identifier can be obtained, and the first file and the second file can be mapped to obtain a network monitoring file.

[0071] In some implementations, the network monitoring task files may be integrated in the order of the task identifiers to obtain a network monitoring file.

[0072] In the above embodiment, the network monitoring file obtained based on the network data file with improved accuracy can further improve the accuracy of the network monitoring file, so that when the network monitoring file is applied to the subsequent analysis process of the communication base station, the corresponding network transmission data can be found according to the collection identifier required for the analysis, which not only improves the speed of analyzing the network transmission data, but also improves the accuracy of the analysis results based on the network monitoring file.

[0073] In some embodiments, the above step S102, based on the device identifier corresponding to each network transmission data and the multiple communication service identifiers corresponding to each network device, divides the multiple network transmission data to determine multiple data subsets, which may include step S1021 and step S1022:

[0074] Step S1021: dividing multiple pieces of network transmission data having the same task identifier based on the device identifiers corresponding to each piece of network transmission data, and determining multiple pieces of network transmission data corresponding to at least one device identifier;

[0075] In some implementations, multiple network transmission data under the same task identifier are divided according to the device identifier, and multiple network transmission data under the same device identifier are obtained separately. In this way, multiple network transmission data corresponding to at least one device identifier can be obtained based on the multiple network transmission data under the same task identifier.

[0076] For example, a data processing method for network transmission data in a DU-CU separation scenario is described, such as Figure 2As shown, it can be seen that in the data processing module, multiple network transmission data with the same task ID are divided according to the secondary anchor point 22, that is, the network element ID. For example, multiple network data with task ID TASK_NUM-N are divided into 4 data sets according to the network element ID. The 4 data sets correspond to 4 secondary anchor points 22, that is, the 4 network element IDs are CU-1, CU-2, DU-1, and DU-2 respectively.

[0077] Step S1022: for each of the plurality of network transmission data corresponding to the device identification, based on the plurality of communication service identifications corresponding to the device identification, a plurality of data subsets are determined.

[0078] In some embodiments, multiple network transmission data under the same device identifier are divided according to the communication service identifier, and the multiple network transmission data under the same communication service identifier are obtained separately, and the multiple network transmission data under the same communication service identifier are determined as a data subset, so that multiple data subsets under the same device identifier can be obtained.

[0079] For example, a data processing method is described for network transmission data in a DU-CU separation scenario, such as Figure 2 As shown, it can be seen that in the data processing module, multiple network transmission data with the same network element ID are divided according to the third-level anchor point 23, that is, the PLMN ID. For example, for multiple network data with the network element ID CU-1, the multiple network data with the network element ID CU-1 are divided into 4 data subsets based on the PLMN ID. The 4 data subsets correspond to 4 third-level anchor points 23, that is, the 4 PLMN IDs are PLMN1, PLMN2, PLMN3, and PLMN4 respectively.

[0080] Furthermore, based on the above method, multiple data subsets corresponding to all device identifiers under the same task identifier can be obtained, so that multiple data subsets under the same task identifier can be obtained.

[0081] In the above embodiment, multiple network transmission data under the same task identifier are divided in sequence according to the device identifier and the communication service identifier, so that the device identifier, communication service identifier and task identifier in the network transmission data in each data subset are the same, so that a collection identifier of the data subset can be generated based on the device identifier and the communication service identifier. The collection identifier serves as index information of the data subset, and when analyzing the network status of the base station, the required data subset can be quickly found based on the collection identifier.

[0082] In some embodiments, the above step S104, based on all data subsets under the same task identifier and the set identifiers corresponding to all data subsets, determines the network data report under the same task identifier, and may include steps S1041 to S1043:

[0083] Step S1041: for each data subset, each network transmission data under the data subset is stored in the order of the communication service identifier of the data subset to obtain a storage file of the data subset;

[0084] Here, the storage file may be implemented in the form of a data table.

[0085] In some implementations, the order of the communication service identifiers may be generated based on an order rule, for example, the order rule may be to sort the identifiers in descending order.

[0086] In some implementations, the order of the communication service identifiers may be preset in the data processing device.

[0087] For example, the storage file of the data subset is used as a data table for explanation, such as Figure 4 As shown, the network transmission data in the data subset is first stored in order according to the communication service identifier, for example, CU1_PLMN1_RRC and CU1_PLMN2_RRC are adjacent positions, and CU2_PLMN1_RRC and CU2_PLMN2_RRC are adjacent positions.

[0088] Step S1042: Based on the device identifiers of all network devices under the same task identifier, the storage files of all data subsets are integrated in the order of all device identifiers under the same task identifier to obtain the storage files of the same task identifier;

[0089] In some implementations, the order of device identifications may be generated based on an order rule.

[0090] In some implementations, the order of the device identifications may be preset in the data processing apparatus.

[0091] For example, the storage file of the data subset is used as a data table for explanation, such as Figure 4 As shown, the network transmission data in the data subset is stored in sequence according to the device identification, for example, CU1_PLMN1_RRC, CU1_PLMN2_RRC and CU2_PLMN1_RRC are adjacent in sequence, and CU1_PLMN2_HO, CU2_PLMN1_HO and CU2_PLMN2_HO are adjacent in sequence.

[0092] In some implementations, network transmission data of the same parameter type may be stored together based on the parameter type in the network transmission data.

[0093] For example, the storage file of the data subset is used as a data table for explanation, such as Figure 4 As shown, the network transmission data in the data subset is stored in order according to the parameter type, for example, the relevant network transmission data with the parameter of RRC is stored first, then the relevant network transmission data with the parameter of HO is stored, and finally the relevant network transmission data with the parameter of PDCP is stored. Among them, for storing multiple network transmission data with the same parameters, they can be stored in order according to different communication service identifiers under the same device identifier, and then stored in order according to different device identifiers. For example, taking the storage parameter as PDCP for explanation, the storage order is CU1_PLMN1_PDCP, CU1_PLMN2_PDCP, CU2_PLMN1_PDCP and CU2_PLMN2_PDCP.

[0094] Step S1043: Based on the storage files under the same task identifier and the set identifiers corresponding to all the data subsets, determine the network data files under the same task identifier.

[0095] In the above embodiment, the network transmission data in the network data file is stored based on the communication identification order and the device identification order, so that the received chaotic network transmission data can be regularly integrated into the network data file, thereby forming a compliant network data file. In this way, when the network data file is used to analyze the communication base station, the analysis time can be reduced and the analysis efficiency can be improved.

[0096] In some embodiments, the above step S103, generating a set identifier of the data subset based on the device identifier and the communication service identifier of the data subset, may include step S1031:

[0097] Step S1031: Generate a set identifier of the data subset based on the device identifier and the communication service identifier of the data subset and the task identifier corresponding to the data subset.

[0098] In the above embodiment, a collection identifier of a data subset is generated based on a device identifier, a communication service identifier, and a task identifier. The collection identifier serves as index information of the data subset. When the network status of the communication base station is subsequently analyzed, the data subset required for the network status analysis can be quickly found based on the collection identifier.

[0099] In some embodiments, before step S101, steps S107 to S109 may be included:

[0100] Step S107: Determine device source information of multiple network devices;

[0101] Here, the device source information refers to the information of the manufacturer that produced the network device.

[0102] Step S108: for each device source information, based on the communication service identifier, the device identifier and the task identifier, determine the data transmission rule corresponding to the device source information; the data transmission rule is used by the network device to encapsulate the collected network data and generate network transmission data;

[0103] Here, since the data formats reported by network devices under different device source information are different, it is necessary to add fields for representing the communication service identifier, device identifier and task identifier on the basis of the data format corresponding to each device source information, so as to generate data transmission rules corresponding to the device source information.

[0104] Step S109: For each piece of device source information, the data transmission rule is sent to the network device corresponding to the device source information.

[0105] In the above embodiment, the data transmission rules corresponding to each device source information are first determined, and then the data transmission rules corresponding to each device source information are sent to the corresponding device, so that the network device encapsulates the collected network data and generates network transmission data. Through this method, the network transmission data can include device identification, communication service identification and task identification, so that the device identification, communication service identification and task identification can be used to realize the division of multiple network transmission data sent by network devices under different device source information.

[0106] The present application embodiment provides a data generation method, such as Figure 5 As shown, the method includes steps S501 to S503:

[0107] Step S501: in response to the triggering of a network monitoring task, obtaining a plurality of network data under a plurality of communication services collected by a network device;

[0108] Step S502: Encapsulating multiple pieces of network data based on data transmission rules to generate multiple pieces of network transmission data;

[0109] Step S503: Send the plurality of network transmission data to the data processing device.

[0110] In an embodiment of the present application, the collected network data is encapsulated through the data transmission rules in the network device to generate network transmission data, so that the network transmission data includes a device identifier, a task identifier and a communication service identifier. In this way, after receiving the network transmission data, the data processing device can process the network transmission data based on the device identifier, task identifier and communication service identifier in the network transmission data, and finally generate a network monitoring file.

[0111] In some embodiments, before step S501, step S504 is further included:

[0112] Step S504: receiving a data transmission rule sent by a data collection module in a data processing device; the data transmission rule at least includes a communication service identifier, a device identifier and a task identifier.

[0113] In the above embodiment, after receiving the data transmission rule sent by the data processing device, the collected network data can be controlled to generate network transmission data according to the data transmission rule and sent to the data processing device.

[0114] The present application embodiment provides a data processing device, such as Figure 6 As shown, including:

[0115] The data collection module 61, the data processing module 62 and the file generation module 63 are connected in sequence; wherein,

[0116] The data collection module 61 is used to receive a plurality of network transmission data respectively sent by a plurality of network devices in response to the triggering of the network monitoring task; the network transmission data is generated based on the data transmission rule; the data transmission rule at least includes a device identifier, a task identifier and a communication service identifier;

[0117] Here, the data collection module also includes a data collection unit, which receives a plurality of network transmission data respectively sent by a plurality of network devices, and sends the received plurality of network transmission data to the data processing module.

[0118] The data processing module 62 is used to obtain multiple network transmission data with the same task identifier; divide the multiple network transmission data based on the device identifier corresponding to each network transmission data and the multiple communication service identifiers corresponding to each network device to determine multiple data subsets; for each data subset, generate a collection identifier of the data subset based on the device identifier and the communication service identifier of the data subset;

[0119] The file generation module 63 is used to determine the network data file under the same task identifier based on all the data subsets under the same task identifier and the set identifiers corresponding to all the data subsets.

[0120] In some embodiments, the data processing module 62 is used to receive multiple network transmission data sent by multiple network devices in response to the triggering of a network monitoring task; based on the task identifier corresponding to each network transmission data, the multiple network transmission data sent by the multiple network devices are divided, and the multiple network transmission data corresponding to at least one task identifier are determined.

[0121] In some embodiments, the file generation module is further used to obtain the network data files corresponding to all the task identifiers respectively; and generate the network monitoring file of the network monitoring task based on all the network data files.

[0122] In some embodiments, the data processing module 62 is used to divide multiple network transmission data with the same task identifier based on the device identifier corresponding to each network transmission data, and determine multiple network transmission data corresponding to at least one device identifier; for the multiple network transmission data corresponding to each device identifier, multiple data subsets are determined based on the multiple communication service identifiers corresponding to the device identifier.

[0123] In some embodiments, the file generation module 63 is used to store, for each data subset, each network transmission data under the data subset in the order of the communication service identifier of the data subset to obtain the storage file of the data subset; based on the device identifier of all network devices under the same task identifier, integrate all the storage files of the data subset in the order of all the device identifiers under the same task identifier to obtain the storage file of the same task identifier; based on the storage files under the same task identifier and the collection identifiers corresponding to all the data subsets, determine the network data file under the same task identifier.

[0124] In some embodiments, the data processing module 62 is used to generate a set identifier of the data subset based on the device identifier and the communication service identifier of the data subset and the task identifier corresponding to the data subset.

[0125] In some embodiments, the data collection module 62 also includes a rule generation unit, which is used to determine the device source information of multiple network devices; for each device source information, based on the communication service identifier, device identifier and task identifier, determine the data transmission rules corresponding to the device source information; the data transmission rules are used by the network device to encapsulate the collected network data and generate network transmission data; for each device source information, send the data transmission rules to the network device corresponding to the device source information.

[0126] The following describes the application of the embodiments of the present application in actual scenarios.

[0127] For commercial 5G base stations, performance files and measurement files are an important function for base station maintenance, network optimization, and customer experience. Performance files can be used to determine the base station status information of the entire 5G base station system, such as UE access success rate, drop rate, switch-in and switch-out conditions, and service quality, making it easier for relevant staff to timely observe the operating status of the 5G base station system and handle maintenance operations.

[0128] With the continuous deployment of 5G base stations, operators require the indicators in performance files and measurement files to be collected on time and with accurate data. At the same time, with the introduction of the Open Radio Access Network (O-RAN) architecture and the Open Test and Integration Center (OTIC) related specifications, the general hardware provided by different suppliers will continue to be compatible with operators, prompting the physical separation or cloud separation of CU and DU devices. Compared with dedicated base stations, the Open Centralized Unit (O-CU) and Open Distributed Unit (O-DU) of general base stations may come from different operators. Combined with the punctual and accurate requirements of PM files and MR files, it will bring great difficulties to the generation of PM files and MR files, which is mainly reflected in the following aspects:

[0129] 1. Existing 5G base stations have not achieved physical separation or cloud separation of O-CU devices and O-DU devices according to the O-RAN architecture.

[0130] 2. Existing 5G base stations do not implement the collection of relevant data of PM files and MR files in multi-task and / or multi-cell scenarios.

[0131] 3. Under the O-RAN architecture, there must be a scenario where an O-CU device is combined with multiple O-DU devices. One O-CU device and multiple O-DU devices may come from different hardware device suppliers. However, the current O-RAN architecture does not propose how to collect and communicate PM data or MR data between CU devices and DU devices.

[0132] 4. Since both the O-CU device and the O-DU device will collect PM data or MR data, the PM data or MR data is relatively scattered. Therefore, it is necessary to associate and integrate these scattered PM data or MR data into a compliant PM file or MR file. However, under the current O-RAN architecture, there is no method in the relevant technology to generate a compliant PM file or MR file.

[0133] Below, taking PM file collection and association as an example, this article focuses on the method of collecting and associating data to form compliant performance files required by operators after the physical separation or cloud separation of O-CU and O-DU devices under the O-RAN architecture.

[0134] First, regarding the physical separation or cloud separation of O-CU and O-DU devices, the existing problems or scenarios are as follows:

[0135] 1. One O-CU device + multiple OD devices U scenario, CU devices and DU devices come from different suppliers. Each service network element device transmits PM data to the operation and maintenance (OM) module at the same time, and the order in which each service network element device transmits data is unpredictable, which will cause confusion in the data received by the OM module. Furthermore, in the combination of multi-task collection scenarios, operators will collect PM files in different time periods and with different indicators according to the business scenarios, resulting in multi-task situations. In this scenario, each service network element will maintain PM data according to each task and transmit data to the OM module when the file cycle arrives. At this time, the OM module will receive PM data in confusion, resulting in the inability to generate PM files normally.

[0136] 2. With the increasing number of business scenarios, in the co-construction and sharing scenario, it is necessary to consider multi-task, multi-cell, and multi-PLMN situations. The PM data collected by the OM module in the co-construction and sharing scenario is large and complex. Therefore, a suitable PM data association method is needed to associate and organize the PM data and write it into the PM file.

[0137] Because the O-CU and O-DU devices can be deployed in various ways after separation, and multiple DU network elements can run in a single DU server. To vividly describe the problem, the PM data reported by network element devices from different vendors after the O-CU and O-DU devices are separated is used as an example.

[0138] During the execution of PM tasks, each service network element reports PM data in the following ways: Figure 3As shown, "TASK1 (PLMN1, PLMN2...)" indicates the PM data reporting of TASK1 in a DU network element of a DU server, and the reported PM data may also include PM parameter statistics of multiple cells and multiple PLMNs. According to the O-RAN architecture, the ellipsis in the figure indicates that there may be multiple O-DU network elements, and also indicates that there may be multiple O-DU servers, but there may be only one CU network element, that is, the Centralized Unit-User Plane (CUUP) network element and the Centralized Unit-Control Plane (CUCP) network element.

[0139] In summary, after the O-CU device and the O-DU device are physically or cloud-separated, since each service network element may come from different suppliers, when there are multiple PM data sources, a data processing module is required to accurately collect the PM data in a short time and distinguish the data source according to the task, cell, PLMN and other information. In addition, in special cases, the PM data is much larger than the number of bytes of a single packet transmitted by the standard network, so the PM data needs to be unpacked and sent and assembled. At this time, the data processing module also needs to perform a cyclic redundancy check (CRC) on each data packet and perform PM data association processing after collecting all the data packets. Therefore, when there are multiple PM tasks, multiple cells, and multiple PLMNs, specific means are required to distinguish PM data from different sources, and temporarily open up memory to store data from specific sources for subsequent association.

[0140] In response to the above problems, Figure 7 As shown, PM data may be DU network elements and CU network elements from different suppliers, and the multiple PM data sent by different network elements include PM data based on different tasks, and the multiple PM data under the same task correspond to PM data under different communication services. This makes the PM data sources received by the OM module multiple and messy. Therefore, the present application proposes to add a key business data processing device in the OM module, wherein the key business data processing device includes a data collection and integration module 71 (i.e., a data collection device), a data processing and association module 72 (i.e., a data processing module) and a file generation module 73. Through the above three modules, the key business data processing device can realize the collection and management of PM data based on the anchor point marking method, wherein the anchor point marking means that for PM data or MR data provided by any supplier, it is necessary to provide the operator with basic information such as task ID, network element ID, PLMN ID, etc.

[0141] In the data collection and integration module 71, first, by negotiating with the downstream network elements (such as O-CU, O-DU), the downstream network elements report the PM data (i.e., network transmission data) according to the above-mentioned anchor mark, and then the data collection and integration module 71 integrates the reported PM data and integrates the PM data of all network elements into the same set. In the data processing and association module 72, by traversing all PM data, the PM data is arranged in a specific order according to the anchor mark information. Finally, the file generation module 73 writes the PM data in a specific order when generating the PM file (i.e., the network data file), ensuring that the LDN in the PM file is aligned with the PM parameter name and parameter value, thereby generating a compliant PM file.

[0142] It should be noted that due to the particularity of PM files or MR files, such as the requirement to report indicator data on the hour and to the second, for business network elements, PM data or MR data are all aggregated to the key business processing module in a very short time, and the key business processing module performs unified correlation processing to finally form a compliant performance file or measurement report file.

[0143] Next, each module in the key business data processing device is introduced in detail.

[0144] like Figure 8 As shown, the data collection and integration module includes an anchoring rule negotiation unit 81 (i.e., a rule generation unit) and a data integration unit 82, wherein the anchoring rule negotiation unit 81 is used to determine the anchoring rules (i.e., data transmission rules) between different suppliers, such as using task ID, network element ID and PLMN ID for anchoring negotiation, and then each network element reports PM data according to the anchoring rule, wherein the PM data may be DU network elements and CU network elements from different suppliers, and the multiple PM data sent by different network elements include PM data based on different tasks, and the multiple PM data under the same task correspond to PM data under different communication services; after each network element reports the PM data according to the anchoring rule, the data integration unit 82 can integrate the PM data reported by all network elements for use by the data processing and association module.

[0145] After the data collection and integration module completes the PM data integration, the data processing and association module uses anchor mark method to achieve data association from three dimensions. The anchor mark method refers to combining the specifications of the 3rd Generation Partnership Project (3GPP) and operators, proposing to use the task ID, network element ID and PLMN service ID as triple anchor points, so that any service network element will report these three elements when reporting data. In the data processing and association unit, such as Figure 2As shown, first, the PM data reported by network elements at all levels are split according to the first-level anchor point 21, and then the PM data under the same task ID are associated and integrated according to the second-level anchor point 22 and the third-level anchor point 23, and the PM data of the same PLMN and the same task reported by the CU network element and the DU network element are associated to generate a corresponding data subset, and LDN data 24 is generated based on the PLMNID, task ID and network element ID of the data subset. Finally, the file generation module 73 associates the LDN data with the corresponding data subsets respectively, and generates the task performance files under the task ID, namely, TASK1 performance file 25 and TASK2 performance file 26.

[0146] During implementation, the data processing and association unit first performs first-level anchor processing on the PM data reported by each network element, that is, storing the PM data of the same task ID in the same temporary space, which can be implemented in a specific data table or other data container; then, PM data association processing is performed based on the second-level anchor network element ID and the third-level anchor PLMN ID to generate multiple data subsets. Finally, the performance file of the task ID is generated based on the multiple data subsets and corresponding LDN data under the same task ID through the file generation module.

[0147] In some implementations, the type of network element corresponding to each network element identifier may also be stored in a performance file. The distinction between types of different network elements may be determined based on parameters in PM data transmitted by the network element. For example, PM data reported by a CU-type network element includes parameters related to Radio Resource Control (RRC) connection and Handover (HO), while PM data reported by a UP-type network element includes parameters related to Packet Data Convergence Protocol (PDCP). Thus, based on the parameters in the PM data, it can be determined which type of network element device the PM data is sent from.

[0148] For example, the data association is described in the scenario of CU cell level, such as Fig. 9 As shown, it may include steps S901 to S905:

[0149] Step S901: Divide PM data and collect them into an array;

[0150] Here, the PM data reported by different network element devices in the PM task are integrated into the same set by the data collection and integration module 71. Then, the data processing and association module divides the PM data reported by the network element devices according to the task ID, network element ID and PLMN ID in the PM data to obtain multiple data subsets, and stores the PM data in the data subsets in the same array.

[0151] Step S902: traverse the array, find all RRC connection related PM data belonging to CUCP and store them;

[0152] Here, the file generation module determines the PM data related to the RRC connection in the PM data in each array and stores them in the corresponding data table in sequence according to the network element ID and the PLMN ID.

[0153] In addition, when storing the corresponding data in the data table, the file generation module associates the RRC connection related parameters corresponding to each PM data with the LDN data corresponding to the data subset to which each PM data belongs.

[0154] Step S903: traverse the array to find and store all HO handover related PM data belonging to CUCP;

[0155] Here, the file generation module determines the PM data related to HO switching in each data and stores it in the corresponding data table in sequence according to the network element ID and the PLMN ID.

[0156] In addition, when storing the corresponding data in the data table, the file generation module associates the HO cut-in related parameters corresponding to each PM data with the LDN data corresponding to the data subset to which each PM data belongs.

[0157] Step S904: traverse the array, find all PDCP-related PM data belonging to CUUP and store them;

[0158] Here, the file generation module determines the PM data related to PDCP in the PM data in each array and stores them in the corresponding data table in sequence according to the network element ID and the PLMN ID.

[0159] In addition, when storing the corresponding data in the data table, the file generation module associates the PDCP-related parameters corresponding to each PM data with the LDN data corresponding to the data subset to which each PM data belongs.

[0160] In this way, when analyzing the acquired PM performance file, the LDN data set associated with the data parameter can be determined according to the data parameter required for task analysis, so as to obtain the corresponding PM data for each LDN data in the LDN data set.

[0161] Step S905: traverse all stored PM data, and control the PM parameters to be written into the file through the current LDN and the total number of LDNs.

[0162] Here, it is explained that based on all the task performance files under the PM task, the PM file (ie, network monitoring file) of the PM task is generated.

[0163] In the above step S905, the PM data is stored in the following order: Figure 4 As shown in the figure, "CU1_PLMN1_RRC" represents the storage of PM parameters related to the RRC connection based on PLMN1 statistics on a network element of CUCP of the CU server, and "UP_PLMN1_PDCP_CU1" represents the storage of PM parameters related to the PDCP layer based on PLMN1 statistics on a network element of CUUP of the CU server.

[0164] In addition, taking the CU cell-level LDN as an example, the generated LDN is explained, where the LDN is mainly generated based on information such as the network element ID and the PLMN ID. For example, in "Ldn: Type=Cell, Mode=SA, gNBID=7, NrCI=163841, CUID=1, PLMN ID=4588303", Type represents the data collection dimension of the task, such as the cell dimension and the base station dimension, and Mode represents the networking mode of the current network, such as independent networking (Standalone, SA), Non-Standalone (non-independent networking, NSA), etc., gNBID represents the ID of the base station, NrCI represents the task ID, and CUID represents the network element ID.

[0165] When PM data is associated, the PM data belonging to the same LDN can be accurately classified together according to the number of LDNs and the total number of LDNs, and reflected in the PM file. During implementation, the current number of LDNs is used to control the writing of PM parameters to the PM file, and the total number of LDNs is used to skip the writing of PM parameters currently counted to the PM file, for example Figure 4 The current LDN number in the traverses from the first RRC storage block to the fourth RRC storage block, first writes the parameters in CU1_PLMN1_RRC to the XML file of the PM, then skips the RRC data block using the total number of LDNs, writes the first HO-related PM parameters to the XML file, and so on. The data of the same PLMN can be combined and the PM parameter name value is aligned with the LDN.

[0166] Next, a specific scenario description is given of the data processing method based on CU-DU separation under the O-RAN architecture. Fig.10As shown, the operator's network management OMC (Operation and Maintenance Center) 101 sends the PM task to the gNB 102 base station. The gNB 102 base station generates the corresponding PM file based on the data processing method for CU-DU separation under the O-RAN architecture described above and uploads it to the operator's network management OMC 101. After being acquired by the operator's network management OMC 101, the PM file can be used for network evaluation and system operation and maintenance.

[0167] Among them, the PM file is mainly used to evaluate the UE's access to the gNB base station and the performance of the gNB base station. It is mainly divided into cell-level PM parameters, DU-related PM parameters, CU-related PM parameters, and PM parameter statistics related to switching in and out and switching in and out of different systems. Among them, the CUDU-related PM parameters will further distinguish between PLMNs for statistics, and some parameters will also distinguish between 5QI statistics, slice statistics, etc.

[0168] In summary, based on the embodiments of the present application, the following beneficial effects can be obtained:

[0169] 1. Propose a key business data processing device, and in the key business data processing device, clearly define the data collection and integration module, data processing and association module and file generation module, which are responsible for the collection, association and integration of key business data such as PM and MR in each network element when the CU device and DU device are physically separated or cloud-based.

[0170] 2. An anchor marking method is proposed, which uses the three elements of task ID, network element ID and PLMN ID as anchor points for key data processing. It is responsible for anchor rule negotiation, data association and processing according to the anchor rules, and solves the problem of accurately associating PM data or MR data in scenarios where the network element reports a lot of PM data or MR data with disordered content.

[0171] It should be noted that in the embodiment of the present application, if the above-mentioned data processing method is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the relevant technology can be embodied in the form of a software product, which is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods of each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a U disk, a mobile hard disk, a read-only memory (ROM), a disk or an optical disk. In this way, the embodiment of the present application is not limited to any specific hardware, software or firmware, or any combination of hardware, software, and firmware.

[0172] An embodiment of the present application provides a computer device, including a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the program, some or all of the steps in the above method are implemented.

[0173] The embodiment of the present application provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, some or all of the steps in the above method are implemented. The computer-readable storage medium can be transient or non-transient.

[0174] An embodiment of the present application provides a computer program, including a computer-readable code. When the computer-readable code is run in a computer device, a processor in the computer device executes some or all of the steps for implementing the above method.

[0175] The embodiment of the present application provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and when the computer program is read and executed by a computer, some or all of the steps in the above method are implemented. The computer program product can be implemented specifically by hardware, software or a combination thereof. In some embodiments, the computer program product is specifically embodied as a computer storage medium, and in other embodiments, the computer program product is specifically embodied as a software product, such as a software development kit (SDK) and the like.

[0176] It should be noted here that the description of the various embodiments above tends to emphasize the differences between the various embodiments, and the same or similar aspects can be referenced to each other. The description of the above device, storage medium, computer program and computer program product embodiments is similar to the description of the above method embodiment, and has similar beneficial effects as the method embodiment. For technical details not disclosed in the embodiments of the device, storage medium, computer program and computer program product of this application, please refer to the description of the method embodiment of this application for understanding.

[0177] It should be noted that Fig.11 A schematic diagram of a hardware entity of a computer device in an embodiment of the present application is shown in FIG. Fig.11 As shown, the hardware entity of the computer device 1100 includes: a processor 1101, a communication interface 1102 and a memory 1103, wherein:

[0178] Processor 1101 generally controls the overall operation of computer device 1100 .

[0179] The communication interface 1102 enables the computer device to communicate with other terminals or servers through a network.

[0180] The memory 1103 is configured to store instructions and applications executable by the processor 1101, and can also cache data to be processed or processed by the processor 1101 and each module in the computer device 1100 (for example, image data, audio data, voice communication data, and video communication data), which can be implemented by flash memory (FLASH) or random access memory (Random Access Memory, RAM). Data transmission can be performed between the processor 1101, the communication interface 1102, and the memory 1103 through the bus 1104.

[0181] It should be understood that "one embodiment" or "an embodiment" mentioned throughout the specification means that specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in various embodiments of the present application, the size of the serial number of each step / process mentioned above does not mean the order of execution, and the execution order of each step / process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present application. The serial numbers of the embodiments of the present application mentioned above are for description only and do not represent the advantages and disadvantages of the embodiments.

[0182] It should be noted that, in this article, the terms "include", "comprises" or any other variations 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. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0183] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0184] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0185] In addition, all functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may be a separate unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0186] A person skilled in the art can understand that all or part of the steps of implementing the above method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiment; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM), magnetic disks or optical disks, etc., various media that can store program codes.

[0187] Alternatively, if the above-mentioned integrated unit of the present application is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can essentially or in other words, the part that contributes to the relevant technology can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods of each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROMs, magnetic disks, or optical disks.

[0188] The above are only implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be covered by the protection scope of the present application.

Claims

1. A data processing method, the method comprising: Get multiple network transmission data with the same task ID; The network transmission data is generated based on the data transmission rule; The data transmission rule includes at least a device identifier, a task identifier and a communication service identifier; Based on the device identifiers corresponding to each piece of the network transmission data and the multiple communication service identifiers corresponding to each network device, the multiple pieces of network transmission data are divided to determine multiple data subsets; For each data subset, generating a set identifier of the data subset based on the device identifier and the communication service identifier of the data subset; Based on all the data subsets under the same task identifier and the set identifiers respectively corresponding to all the data subsets, the network data files under the same task identifier are determined.

2. The method according to claim 1, wherein: The obtaining of multiple pieces of network transmission data having the same task identifier includes: In response to the triggering of the network monitoring task, receiving a plurality of network transmission data respectively sent by a plurality of network devices; Based on the task identifier corresponding to each of the network transmission data, the multiple network transmission data respectively sent by the multiple network devices are divided to determine the multiple network transmission data respectively corresponding to at least one task identifier.

3. The method according to claim 2, wherein: The method further comprises: Get the network data files corresponding to all task identifiers; Based on all network data files, a network monitoring file of the network monitoring task is generated.

4. The method according to any one of claims 1 to 3, wherein: The dividing the plurality of network transmission data based on the device identifiers corresponding to each of the network transmission data and the plurality of communication service identifiers corresponding to each network device to determine the plurality of data subsets includes: Based on the device identification corresponding to each of the network transmission data, the multiple network transmission data with the same task identification are divided to determine the multiple network transmission data corresponding to at least one device identification; For each of the plurality of network transmission data corresponding to the device identification, a plurality of data subsets are determined based on the plurality of communication service identifications corresponding to the device identification.

5. The method according to any one of claims 1 to 3, wherein: The determining of the network data report under the same task identifier based on all the data subsets under the same task identifier and the set identifiers respectively corresponding to all the data subsets includes: For each data subset, each network transmission data under the data subset is stored in the order of the communication service identifier of the data subset to obtain a storage file of the data subset; Based on the device identifiers of all network devices under the same task identifier, the storage files of all data subsets are integrated in the order of all device identifiers under the same task identifier to obtain the storage files of the same task identifier; Based on the storage files under the same task identifier and the set identifiers corresponding to all the data subsets respectively, the network data files under the same task identifier are determined.

6. The method according to any one of claims 1 to 3, wherein: The generating a set identifier of the data subset based on the device identifier and the communication service identifier of the data subset includes: Based on the device identifier and the communication service identifier of the data subset and the task identifier corresponding to the data subset, a set identifier of the data subset is generated.

7. The method according to any one of claims 1 to 3, wherein: The method further comprises: Determine device source information for multiple network devices; For each device source information, based on the communication service identifier, the device identifier and the task identifier, a data transmission rule corresponding to the device source information is determined; the data transmission rule is used by the network device to encapsulate the collected network data and generate network transmission data; For each piece of device source information, the data transmission rule is sent to the network device corresponding to the device source information.

8. A data processing device, comprising: A data collection module, a data processing module and a file generation module, wherein the data collection module, the data processing module and the file generation module are connected in sequence; wherein, The data collection module is used to receive a plurality of network transmission data respectively sent by a plurality of network devices in response to the triggering of the network monitoring task; the network transmission data is generated based on the data transmission rule; the data transmission rule at least includes a device identifier, a task identifier and a communication service identifier; A data processing module, used to obtain multiple network transmission data with the same task identifier; based on the device identifier corresponding to each of the network transmission data and the multiple communication service identifiers corresponding to each network device, divide the multiple network transmission data to determine multiple data subsets; for each data subset, based on the device identifier and communication service identifier of the data subset, generate a collection identifier of the data subset; The file generation module is used to determine the network data file under the same task identifier based on all the data subsets under the same task identifier and the set identifiers corresponding to all the data subsets.

9. A data generation method, the method comprising: In response to the triggering of the network monitoring task, a plurality of network data under a plurality of communication services collected by the network device are obtained; Encapsulating the plurality of network data respectively based on the data transmission rule to generate a plurality of network transmission data; The plurality of network transmission data are sent to a data processing device.

10. The method according to claim 9, wherein: The method further comprises: Receive the data transmission rules sent by the data collection module in the data processing device; the data transmission rules at least include a communication service identifier, a device identifier and a task identifier.

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