CN116567674A

CN116567674A - Data processing method, device, network element and readable storage medium

Info

Publication number: CN116567674A
Application number: CN202310827790.XA
Authority: CN
Inventors: 关迎晖; 伍运珍; 张海平
Original assignee: China Telecom Corp Ltd
Current assignee: China Telecom Corp Ltd
Priority date: 2023-07-07
Filing date: 2023-07-07
Publication date: 2023-08-08
Anticipated expiration: 2043-07-07
Also published as: CN116567674B

Abstract

The application relates to a data processing method, a device, a network element and a readable storage medium, wherein the method comprises the following steps: according to the mode of inquiring the feature declaration database by the target task identification of the target data analysis task, target feature declaration data corresponding to the target task identification can be obtained, and a target acquisition strategy is determined according to the target feature declaration data so as to acquire target data required by the target data analysis task according to the target acquisition strategy. The embodiment of the application can realize data acquisition of different data analysis tasks. In addition, the embodiment of the application can adapt to the data acquisition modes of different equipment vendors, thereby being beneficial to the deployment of the analysis service of the NWDAF network element in different areas.

Description

Data processing method, device, network element and readable storage medium

Technical Field

The present invention relates to the field of network technologies, and in particular, to a data processing method, a device, a network element, and a readable storage medium.

Background

The third generation partnership project (3rd Generation Partnership Project,3GPP) proposes a network data analysis function (network data analytics function, NWDAF) in the fifth generation mobile communication technology (5th Generation MobileCommunication Technology,5G) network architecture, which can improve the intelligent operation capability of the network. In the process of providing analysis service to the outside, the NWDAF network element needs to collect network management data, network data and service data from different network elements respectively, and perform data analysis according to the collected data.

For the collection of network management data, only a data subscription model or a data notification model between NWDAF network elements and operation and maintenance management system (operation administration and maintenance, OAM) network elements is proposed in the 3GPP standard, but a specific collection method is not provided.

Disclosure of Invention

The embodiment of the application provides a data processing method, a device, a network element and a readable storage medium, which can realize data acquisition of different data analysis tasks and are beneficial to deployment of analysis services of an NWDAF network element in different areas.

In a first aspect, the present application provides a data processing method, including:

receiving a target request sent by a consumption network element and used for triggering a network data analysis function NWDAF network element to execute a target data analysis task, and determining a target task identifier of the target data analysis task according to the target request;

inquiring a feature declaration database according to the target task identifier to obtain target feature declaration data corresponding to the target task identifier, wherein a plurality of groups of corresponding relations between the task identifier and the feature declaration data are stored in the feature declaration database, and the target feature declaration data comprise item identifiers of all target data items required to be acquired by a target data analysis task, data types corresponding to all target data items and acquisition indication information corresponding to all target data items;

And determining a target acquisition strategy according to the target feature statement data, and executing a data acquisition flow aiming at the target data analysis task according to the target acquisition strategy.

In one embodiment, the target acquisition policy includes an item identification, a data type, a data source, and an access protocol corresponding to the data source for each target data item.

In one embodiment, the target acquisition policy includes a plurality of sub-policies, wherein each sub-policy includes an item identification of at least one target data item, a data type, a data source, and an access protocol corresponding to the data source; the data sources of the target data items included in each sub-policy are consistent, and the access protocols corresponding to the data sources of the target data items included in each sub-policy are consistent.

In one embodiment, the acquisition indication information includes a network element type of a data source corresponding to the target data item, and determining the target acquisition policy according to the target feature declaration data includes:

for each target data item, determining a data source of the target data item according to the type of the network element and the identification of a target network function NF instance acquired in advance and required by a target data analysis task.

In one embodiment, determining the data source of the target data item according to the network element type and the identifier of the target network function NF instance acquired in advance for the target data analysis task includes:

If the network element type included in the acquisition indication information is an OAM type, determining an OAM network element corresponding to the target network function NF instance according to the identification of the target network function NF instance;

and taking the OAM network element as a data source of the target data item.

In one embodiment, determining the data source of the target data item according to the network element type and the pre-acquired identifier of the target network function NF instance includes:

and if the network element type included in the acquisition indication information is NF type, taking the target network function NF instance as a data source of the target data item according to the identification of the target network function NF instance.

In one embodiment, the collection instruction information further includes an access protocol corresponding to the target data item, and the determining the target collection policy according to the target feature declaration data further includes:

and for each target data item, taking the access protocol corresponding to the target data item as the access protocol corresponding to the data source of the target data item.

In one embodiment, determining a target acquisition strategy based on target feature declaration data includes:

for each target data item, inquiring a preset sub-strategy library according to the item identification of the target data item, the data source corresponding to the target data item and the access protocol; the preset sub-strategy library comprises a plurality of generated preset sub-strategies;

If a preset sub-strategy comprising an item identifier of a target data item, a data source corresponding to the target data item and an access protocol exists in a preset sub-strategy library, the preset sub-strategy is taken as a sub-strategy to which the target data item belongs;

if the preset sub-policy library does not contain the item identification of the target data item, the data source corresponding to the target data item and the preset sub-policy of the access protocol, generating the sub-policy to which the target data item belongs.

In one embodiment, a data acquisition process for a target data analysis task is performed according to a target acquisition strategy, including:

and carrying out data acquisition from different data sources according to each sub-strategy included in the target acquisition strategy.

In one embodiment, data collection from different data sources according to sub-policies included in a target collection policy includes:

for any sub-strategy, establishing connection with a data source according to an access protocol corresponding to the data source of each target data item in the sub-strategy;

candidate data corresponding to the data types of the target data items are collected from the data sources respectively.

In one embodiment, establishing a connection with a data source according to an access protocol corresponding to the data source of each target data item in the sub-policy includes:

Selecting an adaptation plug-in corresponding to the access protocol according to the access protocol corresponding to the data source of each target data item in the sub-strategy;

and establishing connection with a data source by adopting an adapter plug-in.

In one embodiment, the method further comprises:

and obtaining a target analysis strategy according to the acquisition result of the data acquisition.

In one embodiment, the target feature declaration data further includes data enhancement information corresponding to each target data item required to be collected by the target data analysis task, and the target analysis strategy is obtained according to a collection result of data collection, including:

for each target data item, carrying out data enhancement processing on candidate data corresponding to the target data item in the acquisition result according to data enhancement information corresponding to the target data item to obtain target data corresponding to the target data item;

and determining a target analysis strategy according to the item identification corresponding to each target data item, the target data and the identification of the target network function NF instance.

In one embodiment, the method further comprises:

performing data analysis processing according to a target analysis strategy to obtain an analysis result;

and feeding back the analysis result to the consumption network element.

In one embodiment, the method further comprises:

If the item identification and the data type of any target data item in any sub-strategy meet the preset deleting conditions, deleting the item identification and the data type of the target data item in the sub-strategy; the method comprises the steps of presetting a deleting condition, wherein the deleting condition is used for indicating that a target data item does not belong to a data item required to be acquired by any incomplete data analysis task;

and if the item identification and the data type of each target data item in any sub-strategy meet the preset deleting conditions, deleting the sub-strategy.

In one embodiment, the method further comprises:

acquiring task identifiers of a plurality of preset data analysis tasks, item identifiers of a plurality of preset data items required to be acquired by each preset data analysis task, data types corresponding to each preset data item and network element types of data sources corresponding to each preset data item;

for task identifications of each preset data analysis task, determining feature declaration data corresponding to the task identifications according to item identifications, data types and network element types of a plurality of preset data items corresponding to the task identifications;

and analyzing task identifications of the tasks and feature declaration data corresponding to the task identifications according to the preset data to obtain a feature declaration database.

In a second aspect, the present application further provides a data processing apparatus, the apparatus comprising:

The receiving module is used for receiving a target request which is sent by the consumption network element and used for triggering the network data analysis function NWDAF network element to execute a target data analysis task;

the first determining module is used for determining a target task identifier of a target data analysis task according to the target request;

the acquisition module is used for inquiring the feature declaration database according to the target task identifier to obtain target feature declaration data corresponding to the target task identifier, wherein a plurality of groups of corresponding relations between the task identifier and the feature declaration data are stored in the feature declaration database, and the target feature declaration data comprise item identifiers of all target data items required to be acquired by the target data analysis task, data types corresponding to all target data items and acquisition indication information corresponding to all target data items;

the second determining module is used for determining a target acquisition strategy according to the target feature declaration data;

and the acquisition module is used for executing a data acquisition flow aiming at the target data analysis task according to the target acquisition strategy.

In a third aspect, the present application further provides an NWDAF network element, including: a memory storing a computer program and a processor implementing the steps of the method of any one of the above first aspects when the processor executes the computer program.

In a fourth aspect, the present application also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the method of any of the first aspects described above.

According to the data processing method, the device, the network element and the readable storage medium, the target characteristic declaration data corresponding to the target task identification can be obtained by inquiring the characteristic declaration database according to the target task identification of the target data analysis task, and the target acquisition strategy is determined according to the target characteristic declaration data so as to acquire target data required by the target data analysis task according to the target acquisition strategy. Therefore, for the requests of different data analysis tasks, the embodiment of the application can determine the corresponding acquisition strategy, and execute the corresponding data acquisition according to the acquisition strategy, thereby realizing the data acquisition of different data analysis tasks. In addition, in the embodiment of the application, the data acquisition modes of different equipment vendors can be adapted by the mode of inquiring the feature declaration database according to the task identifier to obtain the corresponding feature declaration data and the mode of acquiring the data according to the acquisition strategy determined by the feature declaration data, so that the deployment of the analysis service of the NWDAF network element in different areas is facilitated.

Drawings

Fig. 1 is an application scenario schematic diagram of a data processing method provided in an embodiment of the present application;

FIG. 2 is a flow chart of a data processing method according to an embodiment of the present application;

fig. 3A is a schematic diagram of sub-strategy 1 in the target acquisition strategy provided in the embodiment of the present application;

fig. 3B is a schematic diagram of sub-strategy 2 in the target acquisition strategy provided in the embodiment of the present application;

FIG. 4 is a flow chart of a data processing method according to another embodiment of the present application;

FIG. 5 is a flow chart of a data processing method according to another embodiment of the present application;

FIG. 6 is a flow chart of a data processing method according to another embodiment of the present application;

fig. 7A is a schematic diagram of a target acquisition strategy according to an embodiment of the present application after sub-strategy 1 acquisition is completed;

fig. 7B is a schematic diagram of a target acquisition strategy according to an embodiment of the present application after sub-strategy 2 acquisition is completed;

fig. 8 is a schematic diagram of a target analysis strategy of the target data analysis task 1 according to an embodiment of the present application;

FIG. 9 is a flow chart of a data processing method according to another embodiment of the present application;

FIG. 10 is a flow chart of a data processing method according to another embodiment of the present application;

Fig. 11 is a schematic structural diagram of an NWDAF network element in an embodiment of the present application;

FIG. 12 is a flow chart of a data processing method according to another embodiment of the present application;

FIG. 13 is a flow chart of a data processing method according to another embodiment of the present application;

FIG. 14 is a schematic diagram I of object feature declaration data provided by an embodiment of the present application;

FIG. 15 is a second schematic diagram of object feature declaration data provided in an embodiment of the present application;

FIG. 16 is a schematic diagram of a target acquisition strategy according to an embodiment of the present application after the sub-strategy 1' is acquired;

FIG. 17 is a schematic diagram of a target acquisition strategy according to an embodiment of the present application after the sub-strategy 2' acquisition is completed;

FIG. 18 is a schematic diagram of a target acquisition strategy according to an embodiment of the present application after 3' acquisition of sub-strategies is completed;

fig. 19 is a schematic diagram of a target analysis policy corresponding to an IMS signaling overload analysis task provided in an embodiment of the present application;

fig. 20 is a schematic diagram of a target analysis strategy corresponding to a 5GC single DC fault prediction task provided in an embodiment of the present application;

FIG. 21 is a flow chart of a data processing method according to another embodiment of the present application;

FIG. 22 is a schematic diagram of a data processing apparatus according to one embodiment of the present application;

Fig. 23 is a schematic structural diagram of an NWDAF network element in an embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.

In general, in the process of providing analysis service to the outside, NWDAF network elements need to collect network management data, network data and service data from different network elements respectively, and perform data analysis according to the collected multiple data. The network management data may include, but is not limited to, at least one of the following measurement data (or referred to as performance index data), alarm data (or referred to as fault alarm data), and log data. Network management data is widely used in a large number of NWDAF analysis services.

However, in the data collection and analysis framework defined by the current 3GPP standard, only the collection of network data and service data through an Event open service (Nnf _event exposure_subscriber) of a Network Function (NF) is explicitly defined. However, for the collection of network management data, only a data subscription model or a data notification model between NWDAF network elements and OAM network elements is proposed in the 3GPP standard, but a specific collection method is not provided, and the specific implementation of the equipment manufacturer of NF network elements is relied on.

It should be noted that, in a normal case, the NWDAF network element may collect network management data from the OAM network element corresponding to the NF network element to be collected. When the NWDAF network element provides analysis services for different areas, as the NF network element comes from different equipment vendors, the OAM of the different equipment vendors has data form differences and/or acquisition protocol (or called access protocol) differences, so that the NWDAF network element also needs to adapt to the data acquisition differences of the OAM of a plurality of equipment vendors for the acquisition of network management data of the same analysis service, which increases the difficulty of deployment of the NWDAF network element in analysis services of different areas.

Based on the problems of the related art, the data processing method, the device, the network element and the readable storage medium provided by the embodiment of the application can realize data acquisition of different data analysis tasks and adapt to the data acquisition modes of different equipment vendors by inquiring the feature declaration database according to the task identifier to obtain corresponding feature declaration data and carrying out data acquisition according to the acquisition strategy determined by the feature declaration data, thereby being beneficial to the deployment of the analysis service of the NWDAF network element in different areas.

It should be noted that the beneficial effects or the technical problems to be solved by the embodiments of the present application are not limited to this one, but may be other implicit or related problems, and particularly, reference may be made to the following description of embodiments.

Fig. 1 is a schematic application scenario diagram of a data processing method provided in the embodiment of the present application, and as shown in fig. 1, the application scenario in the embodiment of the present application may include, but is not limited to: a consumer network element 10, an NWDAF network element 11, an OAM network element 12 and a target NF network element 13.

In this embodiment of the present application, the consumer network element 10 may send, to the NWDAF network element 11, a target request for triggering the NWDAF network element to perform a target data analysis task, so that the NWDAF network element 11 performs the data processing method provided in the embodiment of the present application.

In this embodiment of the present application, the NWDAF network element 11 may be collected from the OAM network element 12 or may be collected from the target NF network element 13 required to be collected by the target data analysis task in the process of collecting the target data required to be collected by the target data analysis task. It should be understood that, in the case where the NWDAF network element 11 collects the target data from the OAM network element 12, the OAM network element 12 belongs to a data source corresponding to the target data; in the case where the NWDAF network element 11 collects target data from the target NF network element 13, the target NF network element 13 belongs to a data source corresponding to the target data.

For example, in the case where the target data of the OAM network element cannot meet the analysis service requirement of the NWDAF network element in terms of delay or accuracy, the NWDAF network element 11 may directly collect the target data from the target NF network element that needs to be collected.

Illustratively, the target data related to the embodiment of the present application may include, but is not limited to, network management data, where the network management data may include, but is not limited to, at least one of the following measurement data, alarm data, and log data.

It should be noted that, in the embodiments of the present application, the target data analysis task is referred to as a generic term, and may include one target data analysis task, or may include a plurality of target data analysis tasks. In the case where the target data analysis task includes a plurality of target data analysis tasks, the processing manner of each target data analysis task may refer to the data processing method provided in the embodiment of the present application.

The following describes the technical solutions of the present application and how the technical solutions of the present application solve the above technical problems in detail with specific embodiments. The following embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.

In one embodiment, fig. 2 is a schematic flow chart of a data processing method in one embodiment of the present application, where the embodiment of the present application is described by taking the NWDAF network element in fig. 1 as an example. As shown in fig. 2, the method of the embodiment of the present application may include the following steps:

Step S201, receiving a target request sent by a consumer network element and used for triggering a network data analysis function NWDAF network element to execute a target data analysis task, and determining a target task identifier of the target data analysis task according to the target request.

The task identifier of any data analysis task referred to in the embodiments of the present application may be used to indicate an analysis type of a data analysis service and/or identification information of a consuming network element.

In this step, the NWDAF network element may receive a target request sent by the consumer network element to trigger the NWDAF network element to execute the target data analysis task, and may determine a target task identifier of the target data analysis task according to the target request. The target request can comprise a target task identifier of a target data analysis task; of course, other data analysis parameter information may be included, such as feedback timing parameters of analysis results defined in the 3GPP standard, and the like.

For example, the target request in the embodiments of the present application may be a data analysis request, or a data analysis subscription message, where the data analysis request is a one-time request and the data analysis subscription message is typically a periodic message.

Step S202, inquiring a feature declaration database according to the target task identifier to obtain target feature declaration data corresponding to the target task identifier.

In the feature declaration database in the embodiment of the present application, a plurality of sets of correspondence between task identifiers and feature declaration data may be stored. For example, the feature declaration database stores the correspondence between the task identifier 1 and the corresponding feature declaration data, the correspondence between the task identifier 2 and the corresponding feature declaration data, and the correspondence between the task identifier 3 and the corresponding feature declaration data.

Illustratively, the feature declaration data corresponding to any task identifier in the embodiments of the present application may include: item identification, data type and acquisition indication information of each data item required to be acquired by executing a data analysis task corresponding to the task identification; of course, other information may also be included, such as NF network element types corresponding to each data item, and the like.

Wherein the item identification of any data item may be used to uniquely indicate that data item; the data type of any data item may be used to indicate the data type that needs to be collected by the data analysis task so that candidate data that needs to be collected by the data analysis task may be screened from the raw data of the data source.

The acquisition indication information of any data item can be used to indicate the network element type of the data source to which the data item corresponds, and/or the access protocol. It should be understood that the data source to which any data item corresponds refers to from which network element the data item is collected.

For example, the data types may include, but are not limited to, any of the following: a measurement data type, an alarm data type, and a log data type; the network element type of the data source may include, but is not limited to, an OAM type or an NF type; the access protocol may include, but is not limited to, any of the following: file transfer protocol (File Transfer Protocol, FTP), streaming protocol, simple network management protocol (Simple Network Management Protocol, SNMP).

It should be understood that the network element type of the data source may be used to indicate an OAM collection mode, or an NF network element direct collection mode. If the network element type of the data source is an OAM type, the corresponding acquisition mode is an OAM acquisition mode; if the network element type of the data source is NF type, the corresponding acquisition mode is NF network element direct acquisition mode.

It should be noted that, the data types referred to in the embodiments of the present application may be used to indicate data filtering features, and the acquisition indication information may be used to indicate data acquisition features.

In this step, the NWDAF network element may query the feature declaration database according to the target task identifier, and use feature declaration data corresponding to the target task identifier in the feature declaration database as target feature declaration data.

Illustratively, the object feature declaration data in the embodiments of the present application may include: item identification of each target data item required to be acquired by the target data analysis task, data type corresponding to each target data item and acquisition indication information corresponding to each target data item; of course, other information may also be included, for example, a target NF network element type corresponding to each target data item, and so on.

According to the method, the device and the system, the target data required to be collected by the target data analysis task can be mapped into relevant target data item parameters by inquiring the feature statement database according to the target task identification to obtain the target feature statement data, and the data forms of different equipment vendors can be adapted, so that the problem of data form difference among different equipment vendors can be solved.

Step S203, determining a target acquisition strategy according to the target feature statement data, and executing a data acquisition flow aiming at a target data analysis task according to the target acquisition strategy.

In this step, the NWDAF network element may determine a target acquisition policy according to target feature declaration data corresponding to the target task identifier, and execute a data acquisition procedure for a target data analysis task according to the target acquisition policy; the target acquisition strategy can be used for indicating the acquisition mode of target data required to be acquired for the target data analysis task.

According to the method and the device for acquiring the target data, the target acquisition strategy is determined according to the target feature statement data, and the mode of acquiring the target data according to the target acquisition strategy can be adapted to the data acquisition modes of different equipment vendors, so that the problem of data acquisition difference among different equipment vendors can be solved.

In addition, in the embodiment of the application, by means of a target acquisition strategy, acquisition coordination among a plurality of data analysis tasks can be achieved, so that the same data items required to be acquired by the plurality of data analysis tasks can be prevented from being repeatedly acquired.

According to the data processing method, the target characteristic declaration data corresponding to the target task identification can be obtained by inquiring the characteristic declaration database according to the target task identification of the target data analysis task, and the target acquisition strategy is determined according to the target characteristic declaration data, so that target data required by the target data analysis task can be acquired according to the target acquisition strategy. Therefore, for the requests of different data analysis tasks, the embodiment of the application can determine the corresponding acquisition strategy, and execute the corresponding data acquisition according to the acquisition strategy, thereby realizing the data acquisition of different data analysis tasks. In addition, in the embodiment of the application, the data acquisition modes of different equipment vendors can be adapted by the mode of inquiring the feature declaration database according to the task identifier to obtain the corresponding feature declaration data and the mode of acquiring the data according to the acquisition strategy determined by the feature declaration data, so that the deployment of the analysis service of the NWDAF network element in different areas is facilitated.

In an embodiment, on the basis of the above embodiment, the relevant content of the target acquisition strategy is described in the embodiment of the present application.

The target acquisition policy in the embodiments of the present application may include, but is not limited to, item identification of each target data item, data type, data source, and access protocol corresponding to the data source. Wherein, the item identification and the data type of any target data item can be respectively the same as the item identification and the data type of the target data item in the target feature declaration data; the data source of any target data item and the access protocol to which the data source corresponds may be determined from the acquisition indication information of the target data item in the target feature declaration data.

In a possible implementation manner, the target acquisition policy in the embodiment of the present application may include a plurality of sub-policies, where each sub-policy may include, but is not limited to, an item identifier of at least one target data item, a data type, a data source, and an access protocol corresponding to the data source; the data sources of the target data items included in each sub-policy are consistent, and the access protocols corresponding to the data sources of the target data items included in each sub-policy are consistent. Illustratively, the item identification and data type of any target data item may be in the form of a binary group.

For example, assume that the target acquisition strategy includes: the target data item 1, the target data item 2 and the target data item 3 respectively correspond to item identifiers, data types, data sources and access protocols corresponding to the data sources, wherein the data sources of the target data item 1 are consistent with the data sources of the target data item 3, and the access protocols of the data sources of the target data item 1 are consistent with the access protocols of the data sources of the target data item 3, and then the target acquisition strategy can comprise a first sub-strategy and a second sub-strategy, wherein the first sub-strategy can comprise item identifiers, data types, data sources and access protocols corresponding to the data sources respectively corresponding to the target data item 1 and the target data item 3; the second sub-policy may include an item identifier corresponding to the target data item 2, a data type, a data source, and an access protocol corresponding to the data source.

In this implementation manner, the NWDAF network element may divide the target acquisition policy into a plurality of sub-policies according to the data source and the access protocol of each target data item, where the data source and the access protocol of each target data item included in any sub-policy are consistent, so that one sub-policy is created for each target data item of the same data source and using the same access protocol, so that the subsequent NWDAF network element executes the data acquisition process of the corresponding target data item according to different sub-policies, which is beneficial to improving the data acquisition efficiency.

In one embodiment, on the basis of the above embodiment, the embodiment of the present application describes how to determine, according to the target feature declaration data, the data source and the relevant content of the access protocol of each target data item in the target acquisition policy in step S203.

In a possible implementation manner, in the case that the acquisition indication information corresponding to any target data item includes a network element type of a data source corresponding to the target data item, for each target data item, determining a data source of the target data item according to the network element type and an identifier of a target network function NF instance required to be acquired by a target data analysis task in advance.

In this implementation manner, for each target data item in the target acquisition policy, the NWDAF network element may determine, according to the network element type of the data source corresponding to the target data item in the target feature declaration data and the identifier of the target network function NF instance required to acquire the target data analysis task in advance, the data source of the target data item. The identification of the target network function NF instance required to be acquired by the target data analysis task may be acquired from a network storage function entity NRF network element after the NWDAF network element receives the target request; of course, it may be acquired by other means for NWDAF network elements.

For example, if the network element type included in the collection indication information corresponding to any target data item is an OAM type, the NWDAF network element may determine, according to the identifier of the target NF instance, the OAM network element corresponding to the target NF instance, and use the OAM network element corresponding to the target NF instance as the data source of the target data item. It should be noted that the OAM network elements corresponding to different NF instances may be different, so the NWDAF network element needs to determine the OAM network element corresponding to the target NF instance according to the identifier of the target NF instance.

Still further exemplary, if the network element type included in the acquisition indication information corresponding to the arbitrary target data item is NF type, the NWDAF network element may use the target NF instance as the data source of the target data item according to the identifier of the target NF instance.

In summary, it is known that the data source information of any target data item in any sub-policy in the embodiments of the present application may include, but is not limited to, a network element type of a data source corresponding to the target data item and an identification of a target NF instance.

For ease of understanding, the target acquisition strategy in the following embodiments of the present application is taken as an example, where the target acquisition strategy includes sub-strategy 1 and sub-strategy 2.

Fig. 3A is a schematic diagram of a sub-policy 1 in the target acquisition policy provided in the embodiment of the present application, fig. 3B is a schematic diagram of a sub-policy 2 in the target acquisition policy provided in the embodiment of the present application, and as shown in fig. 3A, a network element type of a data source corresponding to a target data item 1 'and a target data item 2' in the sub-policy 1 is NF type, an identifier of a corresponding target NF instance is an identifier of a target NF instance 1, and an access protocol of a corresponding data source is an access protocol 1.

As shown in fig. 3B, the network element type of the data source corresponding to the target data item 3' in the sub-policy 2 is an OAM type, the identifier of the corresponding target NF instance is the identifier of the target NF instance 2, and the access protocol of the corresponding data source is the access protocol 2. The network element type of the data source corresponding to the target data item 4 'and the target data item 5' in the sub-policy 2 is an OAM type, the identifier of the corresponding target NF instance is the identifier of the target NF instance 3, and the access protocol of the corresponding data source is the access protocol 2.

In another possible implementation manner, in the case that the acquisition indication information corresponding to any target data item further includes an access protocol corresponding to the target data item, for each target data item, the access protocol corresponding to the target data item is used as the access protocol corresponding to the data source of the target data item.

In this implementation manner, for each target data item in the target acquisition policy, the NWDAF network element may declare, according to the target feature, an access protocol corresponding to the target data item in the data as an access protocol corresponding to the data source of the target data item.

It should be noted that, when the acquisition indication information corresponding to any target data item does not include the access protocol corresponding to the target data item, the NWDAF network element may determine, according to the network element type and/or the data type of the data source corresponding to the target data item in the target feature declaration data, the access protocol corresponding to the data source of the target data item.

Of course, the NWDAF network element may also determine the data source and access protocol of each target data item in the target acquisition policy in other ways.

In one embodiment, fig. 4 is a schematic flow chart of a data processing method in another embodiment of the present application, and on the basis of the above embodiment, how to determine the relevant content of the target acquisition policy according to the target feature declaration data in the above embodiment of the present application is described. As shown in fig. 4, the step S203 in the embodiment of the present application may include the following steps:

step S2031, for each target data item, querying a preset sub-policy library according to the item identifier of the target data item, the data source corresponding to the target data item, and the access protocol.

The preset sub-strategy library in the embodiment of the application comprises a plurality of generated preset sub-strategies. It should be noted that any preset sub-policy may be used to indicate at least one data item that needs to be collected by at least one data analysis task.

In this step, for each target data item, the NWDAF network element may query and match, according to the item identifier of the target data item, the data source and the access protocol corresponding to the target data item, the item identifier of each preset data item in the plurality of preset sub-policies in the preset sub-policy library, the data source and the access protocol respectively.

If a preset sub-policy including the item identifier of the target data item, the data source corresponding to the target data item, and the access protocol exists in the preset sub-policy library, executing step S2032; if the preset sub-policy library does not include the item identifier of the target data item, the data source corresponding to the target data item, and the preset sub-policy of the access protocol, step S2033 is executed.

Step S2032, taking the preset sub-policy as the sub-policy to which the target data item belongs.

In this step, since the preset sub-policy library includes the item identifier of the target data item, the data source corresponding to the target data item, and the preset sub-policy of the access protocol, that is, other data analysis tasks have requested to collect the target data item, the NWDAF network element may use the preset sub-policy as the sub-policy to which the target data item belongs, so that repeated collection of the target data item may be avoided.

Step S2033, generating a sub-policy to which the target data item belongs.

In this step, the NWDAF network element may generate the sub-policy to which the target data item belongs, because the preset sub-policy library does not include the item identifier of the target data item, the data source corresponding to the target data item, and the preset sub-policy of the access protocol.

In a possible implementation manner, if a preset sub-policy including a data source and an access protocol corresponding to a target data item exists in a preset sub-policy library, but the preset sub-policy does not include an item identifier of the target data item, the NWDAF network element may add the item identifier and the data type of the target data item to the preset sub-policy, so that each data item with a consistent data source and access protocol may be divided into the same sub-policy, which is favorable for improving data collection efficiency.

In another possible implementation manner, if a preset sub-policy including a data source and/or an access protocol corresponding to the target data item does not exist in the preset sub-policy library, the NWDAF network element may newly establish a sub-policy including at least an item identifier, a data type, a data source and an access protocol of the target data item in the preset sub-policy library.

For example, for each target data item, the NWDAF network element may query whether the preset sub-policy library includes the identifier of the corresponding target NF instance and the preset sub-policy of the access protocol; if the preset sub-policy library does not have the preset sub-policy containing the identifier of the target NF instance and the access protocol, the NWDAF network element may newly establish a sub-policy including at least the item identifier, the data type, the data source and the access protocol of the target data item in the preset sub-policy library.

If the preset sub-policy is stored in the preset sub-policy containing the identifier of the target NF instance and the access protocol, the NWDAF network element may further query whether the preset sub-policy contains the item identifier of the target data item. If the preset sub-policy includes the item identifier of the target data item, the NWDAF network element may use the preset sub-policy as the sub-policy to which the target data item belongs; if the preset sub-policy does not contain the item identifier of the target data item, the NWDAF network element may add the item identifier and the data type of the target data item to the preset sub-policy.

Of course, the NWDAF network element may also generate the sub-policy to which the target data item belongs in other ways.

In summary, in the embodiment of the present application, for each target data item, a preset sub-policy library is queried according to an item identifier of the target data item, a data source corresponding to the target data item, and an access protocol, and different modes are flexibly adopted to determine a sub-policy to which the target data item belongs according to different query results, so that on one hand, repeated collection of the target data item can be avoided, and on the other hand, each data item with consistent data source and access protocol can be divided into the same sub-policy, which is beneficial to improving data collection efficiency.

In one embodiment, fig. 5 is a schematic flow chart of a data processing method according to another embodiment of the present application, and on the basis of the above embodiment, the embodiment of the present application describes how to execute the data collection flow for the target data analysis task according to the target collection policy in the above step S203. As shown in fig. 5, the "data acquisition procedure for performing the task for target data analysis according to the target acquisition policy" in the above-described step S203 of the embodiment of the present application may include the following steps:

In this step, for any sub-policy in the target acquisition policy, the NWDAF network element may perform data acquisition from the data source corresponding to the sub-policy. It should be noted that, in any sub-policy in the embodiment of the present application, the data source and the access protocol corresponding to each target data item are consistent.

It should be understood that if any sub-policy includes a plurality of target data items, the NWDAF network element may collect the plurality of target data items from the data source corresponding to the sub-policy.

In a possible implementation manner, for any sub-policy, a connection is established with a data source according to an access protocol corresponding to the data source of each target data item in the sub-policy, and candidate data corresponding to the data type of each target data item is collected from the data source respectively.

In this implementation manner, for any sub-policy, the NWDAF network element may establish a connection with the data source according to an access protocol corresponding to the data source of each target data item in the sub-policy.

In an exemplary embodiment, the NWDAF network element may select an adaptation plug-in corresponding to the access protocol according to an access protocol corresponding to a data source of each target data item in the sub-policy, and establish a connection with the data source by using the adaptation plug-in corresponding to the access protocol, so that data collection efficiency may be improved.

Further, the NWDAF network element may collect candidate data corresponding to the data types of each target data item from the data source, so as to screen candidate data required to be collected by the target data analysis task from the original data of the data source.

For example, assuming that any sub-policy may include an item identifier corresponding to the target data item 1, a data type, an access protocol corresponding to a data source, and an item identifier corresponding to the target data item 3, a data type, a data source, and an access protocol corresponding to a data source, where the data source of the target data item 1 is consistent with the data source of the target data item 3, and the access protocol of the data source of the target data item 1 is consistent with the access protocol of the data source of the target data item 3, the NWDAF network element may establish a connection with the data source according to the access protocol corresponding to the data source in the sub-policy, and collect candidate data corresponding to the data type of the target data item 1 and candidate data corresponding to the data type of the target data item 3 from the data source.

In summary, in the embodiment of the present application, by performing data collection from different data sources according to each sub-policy included in the target collection policy, since data collection can be performed by adopting a corresponding data collection manner for different data sources, the embodiment of the present application can be beneficial to adapting to data collection manners of different equipment vendors, so as to solve the problem of data collection difference between different equipment vendors. In addition, as all target data items aiming at the same data source can be collected together, the data collection efficiency is improved.

In one embodiment, fig. 6 is a schematic flow chart of a data processing method in another embodiment of the present application, and on the basis of the foregoing embodiment, description is made on how to obtain a target analysis policy according to a collection result collected by the target collection policy and related content of data analysis processing according to the target analysis policy in the embodiment of the present application. As shown in fig. 6, the method of the embodiment of the present application may further include the following steps:

and step S204, obtaining a target analysis strategy according to the acquisition result of the data acquisition.

In this step, the NWDAF network element may obtain, according to the collection result of the data collection procedure for the target data analysis task, a target analysis policy corresponding to the target task identifier. It should be understood that the collection results of the data collection procedure of the target data analysis task in the embodiment of the present application may include, but are not limited to: candidate data corresponding to each target data item collected is indicated by each sub-strategy in the target collection strategy.

For easy understanding, in the following embodiments of the present application, the target acquisition policy includes sub-policy 1 and sub-policy 2 as examples, and each sub-policy after data acquisition is completed is described.

Fig. 7A is a schematic diagram of a target acquisition strategy according to an embodiment of the present application after the acquisition of sub-strategy 1 is completed, and fig. 7B is a schematic diagram of a target acquisition strategy according to an embodiment of the present application after the acquisition of sub-strategy 2 is completed, where, with respect to fig. 3A and 3B, any sub-strategy in an embodiment of the present application includes candidate data corresponding to each target data item.

Illustratively, the target analysis policy corresponding to the target task identifier in the embodiment of the present application may include, but is not limited to: the target data analysis task is used for acquiring the identification of each target NF instance, and the item identification and the target data corresponding to each target data item of each target NF instance.

For ease of understanding, the following embodiments of the present application will take the target analysis policy of the target data analysis task 1 as an example, and describe the target analysis policy.

Fig. 8 is a schematic diagram of a target analysis policy of the target data analysis task 1 provided in the embodiment of the present application, and as shown in fig. 8, the target analysis policy of the target data analysis task 1 may include, but is not limited to: the data acquisition request identification ID 1, the identification of each target NF instance required to be acquired by the target data analysis task 1, and the item identification and the target data corresponding to each target data item of each target NF instance. It should be understood that in the embodiment of the present application, in the case that the NWDAF network element receives the target request for triggering the target data analysis task, the data acquisition request identifier ID 1 corresponding to the target data analysis task may be generated, where the data acquisition request ID 1 may correspond to the target task identifier of the target data analysis task.

In a possible implementation manner, under the condition that the target feature declaration data further comprises data enhancement information corresponding to each target data item required to be acquired by the target data analysis task, for each target data item, performing data enhancement processing on candidate data corresponding to the target data item in an acquisition result according to the data enhancement information corresponding to the target data item, obtaining target data corresponding to the target data item, and determining a target analysis strategy according to item identification corresponding to each target data item, target data and identification of a target NF instance.

The data enhancement information corresponding to any target data item in the embodiment of the present application may include, but is not limited to, a calculation rule and/or an analysis rule; the calculation rule may be used to indicate a calculation manner of the candidate data, so as to obtain corresponding target data; the parsing rules may be used to indicate a parsing scheme for the candidate data, e.g., a parsing scheme for the candidate data or a candidate message to which the candidate data pertains.

It should be noted that, the data enhancement information referred to in the embodiments of the present application may be used to indicate the data enhancement feature.

In this implementation manner, in the case that the target feature declaration data further includes data enhancement information corresponding to each target data item required to be acquired by the target data analysis task, for each target data item, the NWDAF network element may perform corresponding data enhancement processing on candidate data corresponding to the target data item in the acquisition result according to the data enhancement information corresponding to the target data item, so as to obtain target data corresponding to the target data item.

For example, if the data enhancement information corresponding to any target data item includes a calculation rule, the NWDAF network element may perform corresponding data enhancement processing on the candidate data corresponding to the target data item in the collection result according to the calculation rule, so as to obtain target data corresponding to the target data item.

In another example, if the data enhancement information corresponding to any target data item includes an parsing rule, the NWDAF network element may perform corresponding data enhancement processing on the candidate data corresponding to the target data item in the collection result according to the calculation rule, so as to obtain target data corresponding to the target data item.

Further, the NWDAF network element may obtain the target analysis policy according to a preset arrangement rule according to the item identifier corresponding to each target data item, the target data, and the identifier of the target NF instance.

For example, the NWDAF network element may arrange together the target data and the item identifier corresponding to each target data item belonging to the same target NF instance.

For another example, NWDAF network elements may be arranged in order of the identity of the target NF instance from small to large, or in order of the change of the first letter of the identity of the NF instance from a to z.

It should be understood that the NWDAF network element may determine the target analysis policy in case the target data corresponding to each target data item that needs to be collected by the target data analysis task is all completed.

Of course, the NWDAF network element may also obtain the target analysis policy by other manners according to the item identifier corresponding to each target data item, the target data, and the identifier of the target NF instance.

In another possible implementation manner, if the data form of the candidate data corresponding to each target data item in the acquisition result meets the preset requirement, the NWDAF network element may determine the target analysis policy according to the item identifier corresponding to each target data item in the acquisition result, the candidate data, and the identifier of the target NF instance.

Of course, the NWDAF network element may also obtain the target analysis policy by other manners according to the acquisition result of the data acquisition.

Step S205, data analysis processing is carried out according to the target analysis strategy to obtain an analysis result, and the analysis result is fed back to the consumption network element.

In this step, the NWDAF network element may perform data analysis processing according to the target data corresponding to each target data item included in the target analysis policy, to obtain an analysis result of the target data analysis task.

For example, the NWDAF network element may input target data corresponding to each target data item included in the target analysis policy into a preset data analysis model to obtain an analysis result.

Of course, the NWDAF network element may also obtain the analysis result through other data analysis processing according to the target data corresponding to each target data item included in the target analysis policy.

Further, the NWDAF network element may feed back the analysis result to the consumption network element according to the timing indicated by the feedback timing parameter of the analysis result carried in the target request, or the NWDAF network element may feed back the analysis result to the consumption network element according to a preset feedback timing.

In summary, in the embodiment of the present application, the target analysis strategy is obtained according to the acquisition result of data acquisition; further, according to the target analysis strategy, data analysis processing is carried out to obtain an analysis result, and the analysis result is fed back to the consumption network element. In the embodiment of the application, the target analysis strategy contains the target data corresponding to each target data item required to be acquired by the target data analysis task, so that the processing efficiency of data analysis processing is improved according to the target analysis strategy. In addition, in the embodiment of the application, the data acquisition processing and the data analysis processing are loosely coupled by further introducing the target analysis strategy based on the target acquisition strategy, so that the access protocol difference problem among different equipment vendors is solved, and the data processing efficiency is improved.

In one embodiment, fig. 9 is a schematic flow chart of a data processing method in another embodiment of the present application, and on the basis of the above embodiment, a management manner of a sub-policy in the above target acquisition policy is described in the embodiment of the present application. As shown in fig. 9, the method of the embodiment of the present application may further include the following steps:

step S901, deleting the item identifier and the data type of the target data item in the sub-policy if the item identifier and the data type of any target data item in any sub-policy satisfy the preset deletion condition.

The preset deletion condition referred to in the embodiments of the present application may be used to indicate that the target data item does not belong to a data item that needs to be collected for any incomplete data analysis task.

In this step, if the item identifier and the data type of any target data item in any sub-policy satisfy the preset deletion condition, the NWDAF network element may delete the item identifier and the data type of the target data item in the sub-policy.

For example, assuming that the item identification and data type of the target data item 1 in sub-policy 1 does not belong to the item identification and data type of the data item required to be collected by any incomplete data analysis task, but the item identification and data type of the target data item 2 in sub-policy 1 belongs to the item identification and data type of the data item required to be collected by the incomplete data analysis task 3, the NWDAF network element may delete the item identification and data type of the target data item 1 in sub-policy 1.

Step S902, deleting the sub-strategy if the item identification and the data type of each target data item in any sub-strategy meet the preset deletion conditions.

In this step, if the item identifier and the data type of each target data item in any sub-policy satisfy the preset deletion condition, the NWDAF network element may delete the sub-policy.

For example, assuming that sub-policy 1 includes an item identifier, a data type, a data source, and an access protocol corresponding to the data source for target data item 1 and target data item 2, respectively, where the item identifier and the data type of target data item 1 do not belong to the item identifier and the data type of the data item required to be collected for any incomplete data analysis task, and the item identifier and the data type of target data item 2 do not belong to the item identifier and the data type of the data item required to be collected for the incomplete data analysis task, NWDAF network element may delete sub-policy 1.

In summary, in the embodiment of the application, by adopting different deletion management modes according to whether the item identifier and the data type of each target data item in the sub-strategy meet the preset deletion conditions, the sub-strategy that only the target data item to be acquired belongs to is realized, so that useless data acquisition can be avoided, and the data acquisition efficiency is improved.

In one embodiment, fig. 10 is a schematic flow chart of a data processing method in another embodiment of the present application, and on the basis of the foregoing embodiment, description is made in the embodiment of how to obtain relevant contents of the feature declaration database. As shown in fig. 10, the method of the embodiment of the present application may further include the following steps:

step S1001, acquiring task identifiers of a plurality of preset data analysis tasks, item identifiers of a plurality of preset data items required to be acquired by each preset data analysis task, data types corresponding to each preset data item, and network element types of data sources corresponding to each preset data item.

In this step, the NWDAF network element may obtain task identifiers of a plurality of preset data analysis tasks, item identifiers of a plurality of preset data items required to be acquired by each preset data analysis task, data types corresponding to each preset data item, and network element types of data sources corresponding to each preset data item.

In one possible implementation manner, the NWDAF network element may receive task identifiers of the plurality of preset data analysis tasks, item identifiers of a plurality of preset data items required to be acquired by each preset data analysis task, a data type corresponding to each preset data item, and a network element type of a data source corresponding to each preset data item, which are sent by other devices.

In another possible implementation manner, the NWDAF network element may obtain, from a preset storage location, a task identifier of the plurality of preset data analysis tasks, an item identifier of a plurality of preset data items required to be acquired by each preset data analysis task, a data type corresponding to each preset data item, and a network element type of a data source corresponding to each preset data item.

Of course, the NWDAF network element may also obtain the above information in other ways.

Step S1002, for each preset data, analyzing task identifiers of the tasks, and determining feature declaration data corresponding to the task identifiers according to item identifiers, data types and network element types of a plurality of preset data items corresponding to the task identifiers.

In this step, for the task identifier of each preset data analysis task, the NWDAF network element may determine feature declaration data corresponding to the task identifier according to item identifiers, data types, and network element types of a plurality of preset data items corresponding to the task identifier.

For each task identifier, the NWDAF network element may obtain, according to item identifiers and data types of a plurality of preset data items corresponding to the task identifier, item identifiers and data types of a plurality of preset data items included in feature declaration data corresponding to the task identifier, respectively.

Further, the NWDAF network element may obtain, according to the data types and/or the network element types of the plurality of preset data items corresponding to the task identifier, acquisition indication information respectively corresponding to the plurality of preset data items included in the feature declaration data corresponding to the task identifier.

It should be understood that, in the case that the feature declaration data corresponding to any task identifier further includes the NF network element type corresponding to each preset data item, in step S1001, the NF network element type corresponding to each preset data item that needs to be collected by each preset data analysis task is also required to be obtained.

Step S1003, analyzing task identifications of tasks and feature declaration data corresponding to the task identifications according to the preset data to obtain a feature declaration database.

In this step, the NWDAF network element may obtain a feature declaration database according to the task identifier of each preset data analysis task and feature declaration data corresponding to each task identifier, where the feature declaration database may store a correspondence between task identifiers of multiple groups of preset data analysis tasks and corresponding feature declaration data.

In summary, in the embodiment of the present application, a manner of a feature declaration database is determined according to task identifiers of a plurality of preset data analysis tasks, item identifiers of a plurality of preset data items required to be acquired by each preset data analysis task, data types corresponding to each preset data item, and network element types of data sources corresponding to each preset data item, so that corresponding feature declaration data can be queried according to task identifiers for different data analysis tasks, and data acquisition can be performed according to an acquisition policy determined by the feature declaration data, thereby realizing data acquisition of different data analysis tasks.

In one embodiment, fig. 11 is a schematic structural diagram of an NWDAF network element in one embodiment of the present application, and on the basis of the foregoing embodiment, the data processing method combined with the NWDAF network element in the embodiment of the present application divides the structure of the NWDAF network element into different functional modules. As shown in fig. 11, NWDAF network elements of the embodiments of the present application may include, but are not limited to: an analysis reasoning module 1101, a data access module 1102 and an acquisition execution module 1103. Wherein, the analysis reasoning module 1101 can be used for providing data analysis service and/or data prediction service to the outside; of course, it can also be used to provide other reasoning services.

The data access module 1102 may perform feature declaration according to task identifiers of a plurality of preset data analysis tasks sent by the analysis reasoning module 1101, item identifiers of a plurality of preset data items required to be acquired by each preset data analysis task, data types corresponding to each preset data item, and network element types of data sources corresponding to each preset data item, so as to obtain a feature declaration database, so that target data items required to be acquired by different target data analysis tasks may be mapped into relevant target data item parameters.

Further, the data access module 1102 may further determine a target acquisition policy corresponding to the target task identifier according to the target task identifier and the feature declaration database of the target data analysis task, and send the target acquisition policy to the acquisition execution module 1103, so that the acquisition execution module 1103 executes a data acquisition flow for the target data analysis task according to the target acquisition policy.

Further, the data access module 1102 may further determine a target analysis policy according to the collection result returned by the collection executing module 1103, and send the target analysis policy to the analysis reasoning module 1101.

The analysis reasoning module 1101 may perform data analysis according to the target analysis policy sent by the data access module 1102 to obtain an analysis result, and feed back the analysis result to the consumer network element.

It should be noted that, for specific implementation manner, reference may be made to the related content in the foregoing embodiment, which is not described herein again.

In summary, in the embodiment of the present application, by dividing the structure of the NWDAF network element into different functional modules and combining the target acquisition policy and the target analysis policy, loose coupling is implemented between the analysis processing, the data access and the data acquisition, which is beneficial to solving the problem of access protocol differences between different vendors. In addition, by introducing the feature declaration database, the data items required to be collected by different data analysis tasks can be mapped into related data item parameters, so that the problem of data variability among different equipment vendors can be solved. In summary, the embodiment of the application solves the problems of data difference and protocol difference generated by equipment manufacturer difference in the process of acquiring network management data by the NWDAF network element in a lightweight adaptation mode, thereby being capable of promoting the convenient and rapid deployment and external provision of the analysis service of the NWDAF network element.

In one embodiment, fig. 12 is a schematic flow chart of a data processing method in another embodiment of the present application, and on the basis of the foregoing embodiment, in this embodiment of the present application, a description is made on how to obtain relevant contents of the feature declaration database by combining the foregoing analysis reasoning module 1101 and the data access module 1102. As shown in fig. 12, the method of the embodiment of the present application may further include the following steps:

step S1201, the analysis inference module 1101 sends a data item registration request to the data access module 1102.

Illustratively, the data item registration request may include, but is not limited to, the following information:

a) Task identifiers of a plurality of preset data analysis tasks; b) Item identification of a plurality of preset data items required to be acquired by each preset data analysis task: c) Network element types of data sources corresponding to the preset data items; d) The data types corresponding to the preset data items.

In step S1202, the data access module 1102 performs feature declaration on each preset data item of each preset data analysis task, to obtain a feature declaration database.

Wherein, the feature declaration information of any preset data item for any preset data analysis task may include, but is not limited to, the following information:

a) A data type, wherein the data type is used for indicating a data screening feature; b) Data enhancement information, wherein the data enhancement information is used for indicating data enhancement characteristics; c) And collecting indication information, wherein the collection indication information is used for indicating data collection characteristics.

In step S1203, the data access module 1102 sends a data item registration reply to the analysis inference module 1101, where the data item registration reply is used to indicate that the feature declaration has been completed.

In the embodiment of the application, the characteristic statement database is obtained by carrying out characteristic statement on each preset data item of each preset data analysis task in advance, so that corresponding characteristic statement data can be queried according to task identification for different data analysis tasks, and data acquisition can be carried out according to an acquisition strategy determined by the characteristic statement data, thereby realizing data acquisition of different data analysis tasks.

In an embodiment, fig. 13 is a schematic flow chart of a data processing method in another embodiment of the present application, and based on the foregoing embodiment, in this embodiment of the present application, an NWDAF network element includes an analysis reasoning module, a data access module, and an acquisition execution module, and relevant contents of the foregoing data processing method are described in connection with a consumption network element, an NWDAF network element, an NRF network element, a data source, and the like. As shown in fig. 13, the method of the embodiment of the present application may include the following steps:

And step S1301, the consumption network element sends a target request to an analysis reasoning module in the NWDAF network element.

Illustratively, the target request may include a target task identifier of the target data analysis task, so that the network data analysis function NWDAF network element may be triggered to perform the target data analysis task; of course, other data analysis parameter information may also be included.

Step S1302, the analysis reasoning module generates a request identification ID and sends a request confirmation message to the consumption network element under the condition of receiving the target request.

Step S1303, the analysis reasoning module sends an NF discovery request to the NRF network element, so as to acquire the identity of the target network function NF instance required to be acquired by the target data analysis task.

Step 1304, an analysis reasoning module receives an identifier of a target network function NF instance returned by the NRF network element.

Step S1305, the analysis reasoning module sends a target acquisition request to the data access module.

For example, the target acquisition request in the embodiments of the present application may be a data acquisition request, or a data acquisition subscription message.

The target acquisition request in the embodiment of the application may include, but is not limited to, at least one of the following data acquisition parameters:

a) A target task identification; b) At least one NF message, wherein the NF message may comprise an identification of the target NF instance; of course, other NF information, such as the target NF element type, etc., may also be included; c) Acquisition duration, wherein the acquisition duration may be used to indicate a start time, an end time, and/or an acquisition period (e.g., 1 minute or 5 minutes, etc.) of data acquisition; d) The data access module can be used for directly sending the target analysis strategy to the analysis reasoning module, or can be used for on-line storage device for data analysis model reasoning or can be used for off-line storage device for data analysis model training.

Step S1306, when receiving the target acquisition request, the data access module generates a data acquisition request identifier ID, and sends a data request confirmation message to the analysis reasoning module.

It should be noted that, in the embodiment of the present application, the data acquisition request identifier may correspond to the target task identifier.

In step S1307, the data access module may determine a target acquisition policy according to the target task identifier, the identifier of the target NF instance, and the feature declaration database.

Illustratively, the data access module may query the feature declaration database according to the target task identifier to obtain target feature declaration data corresponding to the target task identifier, and determine the target acquisition policy according to the target feature declaration data and the identifier of the target NF instance.

For ease of understanding, in the embodiments of the present application, the target feature declaration data is described by taking an example that the target data analysis task includes an IP multimedia system (IP Multimedia Subsystem, IMS) signaling overload analysis task and a 5G core network (5 gcore,5 gc) single Data Center (DC) fault prediction task.

Fig. 14 is a schematic diagram of target feature declaration data provided in the embodiment of the present application, as shown in fig. 14, the target feature declaration data corresponding to the target task identifier 1 of the IMS signaling overload analysis task may include, but is not limited to, an item identifier of each target data item required to be collected by the IMS signaling overload analysis task, a data type, collection indication information, and a target NF network element type corresponding to each target data item, where the collection indication information may be used to indicate a network element type of a data source corresponding to the target data item, and/or an access protocol.

It should be understood that if the network element type of the data source is an OAM type, the corresponding acquisition mode is an OAM acquisition mode; if the network element type of the data source is NF type, the corresponding acquisition mode is NF network element direct acquisition mode.

Fig. 15 is a schematic diagram two of target feature declaration data provided in the embodiment of the present application, and as shown in fig. 15, target feature declaration data corresponding to a target task identifier 2 of a 5GC single DC fault prediction task may include, but is not limited to, an item identifier, a data type, acquisition indication information, and a target NF network element type corresponding to each target NF item of each target NF instance required to be acquired by the 5GC single DC fault prediction task.

The target acquisition policy in the embodiment of the application may include, but is not limited to, a plurality of sub-policies, where each sub-policy may include, but is not limited to, an item identifier of at least one target data item, a data type, a data source, and an access protocol corresponding to the data source. It should be noted that the data source of any target data item may include, but is not limited to, the identity of the target NF instance and the network element type of the data source.

Illustratively, the data sources of the target data items included in each sub-policy are consistent, and the access protocols corresponding to the data sources of the target data items included in each sub-policy are consistent.

For easy understanding, in the embodiment of the present application, the target data analysis task includes an IMS signaling overload analysis task and a 5GC single DC fault prediction task as examples, and each sub-policy in the target acquisition policy after the data acquisition is completed is described.

Fig. 16 is a schematic diagram of a sub-policy 1 'in a target acquisition policy provided in the embodiment of the present application after the acquisition is completed, where, as shown in fig. 16, a network element type of a data source corresponding to a session completing rate and an initial registration success rate in the sub-policy 1' is an NF type, an identifier of a corresponding target NF instance is S-CSCF01, and an access protocol of the corresponding data source is an FTP protocol.

Fig. 17 is a schematic diagram of a sub-policy 2 'in the target acquisition policy provided in the embodiment of the present application after the acquisition is completed, as shown in fig. 17, a network element type of a data source corresponding to the overload of the memory usage and the overload of the CPU usage in the sub-policy 2' is an NF type, an identifier of a corresponding target NF instance is S-CSCF01, and an access protocol of the corresponding data source is a streaming protocol.

Fig. 18 is a schematic diagram of a sub-policy 3 'in a target acquisition policy provided in the embodiment of the present application after the acquisition is completed, where, as shown in fig. 18, a network element type of a data source corresponding to an initial registration success rate and a mobility registration success rate in the sub-policy 3' is an OAM type, an identifier of a corresponding target NF instance is AMF01, and an access protocol of the corresponding data source is an FTP protocol. The network element type of the data source corresponding to the protocol data unit (Protocol Data Unit, PDU) activation request times and the PDU real-time session numbers in the sub-policy 3' is also an OAM type, the identifier of the corresponding target NF instance is SMF01, and the access protocol of the corresponding data source is also an FTP protocol.

In this embodiment of the present application, for each target data item, the data access module may query a preset sub-policy repository according to an item identifier of the target data item, a data source corresponding to the target data item, and an access protocol, so as to determine whether the preset sub-policy repository includes a sub-policy corresponding to the target data item.

If a preset sub-policy library contains an item identifier of a target data item, a data source corresponding to the target data item and a preset sub-policy of an access protocol, the data access module can take the preset sub-policy as a sub-policy to which the target data item belongs; if the preset sub-policy library does not contain the item identifier of the target data item, the data source corresponding to the target data item and the preset sub-policy of the access protocol, the data access module can generate the sub-policy to which the target data item belongs.

Step S1308, the data access module may send the target acquisition policy to the acquisition execution module.

Step S1309, the acquisition execution module performs data acquisition from different data sources according to each sub-policy included in the target acquisition policy.

For any sub-policy, the collection execution module may establish a connection with the data source according to an access protocol corresponding to the data source of each target data item in the sub-policy, and collect candidate data corresponding to the data type of each target data item from the data source.

Step S1310, the acquisition execution module returns an acquisition result to the data access module.

Step S1311, the data access module performs data enhancement processing on candidate data corresponding to each target data item in the collection result according to the data enhancement information in the target feature declaration data, so as to obtain target data corresponding to each target data item, and marks the data request identifier ID to which each target data item belongs.

In step S1312, the data access module determines, when all the target data corresponding to each target data item required to be collected by the target data analysis task is completed, a target analysis policy according to the item identifier corresponding to each target data item, the target data and the identifier of the target NF instance.

Illustratively, the target analysis policy corresponding to the target task identifier in the embodiment of the present application may include, but is not limited to: the data acquisition request identification ID, the identification of each target NF instance required to be acquired by the target data analysis task, and the item identification and target data corresponding to each target data item of each target NF instance. The item identification and the target data of any target NF instance and the corresponding target data item can be in a triplet form.

For easy understanding, in the embodiment of the present application, the target data analysis task includes an IMS signaling overload analysis task and a 5GC single DC fault prediction task, which are taken as examples, and a target analysis policy is described.

Fig. 19 is a schematic diagram of a target analysis policy corresponding to an IMS signaling overload analysis task provided in an embodiment of the present application, and as shown in fig. 19, the target analysis policy corresponding to the IMS signaling overload analysis task may include, but is not limited to: the method comprises the steps of acquiring a data acquisition request ID 1, identifying each target NF instance required to be acquired by an IMS signaling overload analysis task, and identifying each item corresponding to each target data item of each target NF instance and target data.

Fig. 20 is a schematic diagram of a target analysis policy corresponding to a 5GC single DC fault prediction task provided in an embodiment of the present application, and as shown in fig. 20, the target analysis policy corresponding to the 5GC single DC fault prediction task may include, but is not limited to: the data acquisition request ID 2 and the identification of each target NF instance required to be acquired by the 5GC single DC fault prediction task, and the item identification and the target data corresponding to each target data item of each target NF instance.

Step S1313, the data access module returns the target analysis policy to the analysis reasoning module.

And step 1314, the analysis reasoning module performs data analysis processing according to the target analysis strategy to obtain an analysis result, and feeds back the analysis result to the consumption network element.

In summary, in the embodiment of the present application, by introducing a feature declaration, a problem of data variability between different vendors may be masked, so as to implement lightweight adaptation to devices of different vendors. In addition, by combining the target acquisition strategy and the target analysis strategy, loose coupling of analysis processing, data access and data acquisition is realized, and the problem of access protocol difference among different equipment vendors is solved. In summary, the embodiment of the application can quickly access network management data of different equipment vendors in a lightweight adaptation mode, so that quick deployment and external provision of analysis services of the NWDAF network element can be promoted. In addition, aiming at the data acquisition process of a plurality of data analysis tasks, in the embodiment of the application, the data acquisition coordination can be realized by the mode of carrying out data acquisition according to the target acquisition strategy, so that repeated data acquisition is avoided.

In an embodiment, fig. 21 is a schematic flow chart of a data processing method in another embodiment of the present application, and in the embodiment of the present application, on the basis of the embodiment shown in fig. 13, in the case that an acquisition execution module 1103 includes a plurality of adaptation plug-ins corresponding to access protocols, description is made on how to perform data acquisition from different data sources according to each sub-policy included in a target acquisition policy in step SS 1309. As shown in fig. 21, on the basis of the embodiment shown in fig. 13, the step S1309 described above in the embodiment of the present application may include the steps of:

In step S1309A, for any sub-policy, the acquisition execution module may select an adaptation plug-in corresponding to the access protocol according to the access protocol corresponding to the data source of each target data item in the sub-policy, and establish connection with the data source by adopting the adaptation plug-in.

In step S1309B, the acquisition execution module may screen the candidate data corresponding to the data type of each target data item from the raw data acquired from the data source and returned by the adapter plug-in.

It should be noted that, the specific limitation of each step in the embodiment of the present application may be referred to above for the related content in the embodiment of fig. 5, and the principle and technical effects thereof are similar, which is not repeated herein.

In summary, in the embodiment of the application, the data acquisition efficiency is improved by selecting the mode of performing data acquisition by the adapting plug-in unit corresponding to the access protocol.

It should be understood that, although the steps in the above-described flowcharts are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described above may include a plurality of steps or stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of execution of the steps or stages is not necessarily sequential, but may be performed in turn or alternately with at least a part of other steps or stages.

In one embodiment, fig. 22 is a schematic structural diagram of a data processing device in one embodiment of the present application, where the data processing device provided in the embodiment of the present application may be applied to an NWDAF network element. As shown in fig. 22, the data processing apparatus of the embodiment of the present application may include: a receiving module 2201, a first determining module 2202, a first acquiring module 2203, a second determining module 2204 and an acquiring module 2205.

The receiving module 2201 is configured to receive a target request sent by a consumer network element and used to trigger a network data analysis function NWDAF network element to execute a target data analysis task;

a first determination module 2202 configured to determine a target task identifier of a target data analysis task according to the target request;

the first obtaining module 2203 is configured to query a feature declaration database according to a target task identifier to obtain target feature declaration data corresponding to the target task identifier, where the feature declaration database stores multiple sets of correspondence between the task identifier and the feature declaration data, where the target feature declaration data includes item identifiers of target data items required to be collected by the target data analysis task, data types corresponding to the target data items, and collection indication information corresponding to the target data items;

A second determining module 2204, configured to determine a target acquisition policy according to the target feature declaration data;

the collection module 2205 is configured to execute a data collection procedure for the target data analysis task according to the target collection policy.

In one embodiment, the target acquisition policy comprises a plurality of sub-policies, wherein each sub-policy comprises an item identification of at least one target data item, a data type, a data source, and an access protocol to which the data source corresponds; the data sources of the target data items included in each sub-policy are consistent, and the access protocols corresponding to the data sources of the target data items included in each sub-policy are consistent.

In one embodiment, the collecting indication information includes a network element type of a data source corresponding to the target data item, and the second determining module 2204 includes:

the first determining unit is used for determining the data source of each target data item according to the network element type and the identification of the target network function NF instance acquired in advance and required by the target data analysis task.

In one embodiment, the first determining unit is specifically configured to:

If the network element type included in the acquisition indication information is an OAM type, determining an OAM network element corresponding to the target NF instance according to the identification of the target NF instance;

and taking the OAM network element as a data source of the target data item.

In one embodiment, the first determining unit is specifically configured to:

and if the network element type included in the acquisition indication information is NF type, taking the target NF instance as a data source of the target data item according to the identification of the target NF instance.

In one embodiment, the collection instruction information further includes an access protocol corresponding to the target data item, and the second determining module 2204 further includes:

and the second determining unit is used for regarding the access protocol corresponding to the target data item as the access protocol corresponding to the data source of the target data item for each target data item.

In one embodiment, the second determining module 2204 is specifically configured to:

In one embodiment, the acquisition module 2205 is specifically configured to:

In one embodiment, the acquisition module 2205 comprises:

the establishing unit is used for establishing connection with the data sources according to the access protocols corresponding to the data sources of the target data items in any sub-strategy;

and the acquisition unit is used for respectively acquiring candidate data corresponding to the data types of the target data items from the data sources.

In an embodiment, the establishing unit is specifically configured to:

and establishing connection with a data source by adopting an adapter plug-in.

In one embodiment, the data processing apparatus further comprises:

and the third determining module is used for obtaining a target analysis strategy according to the acquisition result of the data acquisition.

In one embodiment, the target feature declaration data further includes data enhancement information corresponding to each target data item required to be collected by the target data analysis task, and the third determining module is specifically configured to:

and determining a target analysis strategy according to the item identification corresponding to each target data item, the target data and the identification of the target NF instance.

In one embodiment, the data processing apparatus further comprises:

the processing module is used for carrying out data analysis processing according to the target analysis strategy to obtain an analysis result;

and the sending module is used for feeding back the analysis result to the consumption network element.

In one embodiment, the data processing apparatus further comprises:

the first deleting module is used for deleting the item identification and the data type of the target data item in any sub-strategy if the item identification and the data type of any target data item in any sub-strategy meet the preset deleting conditions; the method comprises the steps of presetting a deleting condition, wherein the deleting condition is used for indicating that a target data item does not belong to a data item required to be acquired by any incomplete data analysis task;

and the second deleting module is used for deleting the sub-strategy if the item identification and the data type of each target data item in any sub-strategy meet the preset deleting conditions.

In one embodiment, the data processing apparatus further comprises:

the second acquisition module is used for acquiring task identifiers of a plurality of preset data analysis tasks, item identifiers of a plurality of preset data items required to be acquired by each preset data analysis task, data types corresponding to each preset data item and network element types of data sources corresponding to each preset data item;

a fourth determining module, configured to analyze, for each preset data, a task identifier of a task, and determine feature declaration data corresponding to the task identifier according to item identifiers, data types, and network element types of a plurality of preset data items corresponding to the task identifier;

and a fifth determining module, configured to analyze task identifiers of the tasks and feature declaration data corresponding to the task identifiers according to each preset data, and obtain a feature declaration database.

In the embodiments of the present application, reference may be made to the above definition of a data processing method for specific definition of a data processing apparatus, and the implementation principle and technical effects are similar, and are not repeated herein. Each of the modules in the above-described data processing apparatus may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the NWDAF network element, or may be stored in software in a memory in the NWDAF network element, so that the processor invokes and executes operations corresponding to the above modules.

In an embodiment, fig. 23 is a schematic structural diagram of an NWDAF network element in an embodiment of the present application, as shown in fig. 23, where the NWDAF network element provided in the embodiment of the present application may include a memory 2301 and a processor 2302, where a computer program is stored in the memory 2301, and when the processor 2302 executes the computer program, the implementation principle and technical effect of the implementation scheme in the foregoing data processing method embodiment of the present application are similar, and are not repeated herein.

In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, where the computer program when executed by a processor implements the technical solution in the foregoing data processing method embodiment of the present application, and the implementation principle and technical effect are similar, and are not repeated herein.

In one embodiment, a computer program product is provided, where the computer program is implemented by a processor to implement a technical solution in the foregoing data processing method embodiment of the present application, and the implementation principle and technical effects are similar, and are not repeated herein.

Those skilled in the art will appreciate that implementing all or part of the above-described methods in accordance with the embodiments may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, or the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (DynamicRandom Access Memory, DRAM), and the like.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The foregoing examples represent only a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.

Claims

1. A method of data processing, the method comprising:

inquiring a feature declaration database according to the target task identifier to obtain target feature declaration data corresponding to the target task identifier, wherein a plurality of groups of corresponding relations between the task identifier and the feature declaration data are stored in the feature declaration database, and the target feature declaration data comprise item identifiers of all target data items required to be acquired by the target data analysis task, data types corresponding to all the target data items and acquisition indication information corresponding to all the target data items;

And determining a target acquisition strategy according to the target feature declaration data, and executing a data acquisition flow aiming at the target data analysis task according to the target acquisition strategy.

2. The method of claim 1, wherein the target acquisition policy includes an item identification for each of the target data items, a data type, a data source, and an access protocol corresponding to the data source.

3. The method of claim 2, wherein the target acquisition policy comprises a plurality of sub-policies, wherein each of the sub-policies comprises an item identification of at least one of the target data items, a data type, a data source, and an access protocol corresponding to the data source; the data sources of the target data items included in the sub-policies are consistent, and the access protocols corresponding to the data sources of the target data items included in the sub-policies are consistent.

4. A method according to claim 3, wherein the acquisition indication information comprises a network element type of a data source corresponding to the target data item, and the determining a target acquisition policy according to the target feature declaration data comprises:

and for each target data item, determining a data source of the target data item according to the network element type and the identification of a target network function NF instance acquired in advance and required by the target data analysis task.

5. The method according to claim 4, wherein determining the data source of the target data item according to the network element type and the identity of the target network function NF instance acquired in advance for the target data analysis task comprises:

and taking the OAM network element as a data source of the target data item.

6. The method according to claim 4, wherein said determining a data source of said target data item based on said network element type and a pre-acquired identity of a target network function NF instance comprises:

and if the network element type included in the acquisition indication information is NF type, using the target network function NF instance as a data source of the target data item according to the identification of the target network function NF instance.

7. The method according to any one of claims 4-6, wherein the acquisition indication information further comprises an access protocol corresponding to the target data item, and wherein determining a target acquisition policy according to the target feature declaration data further comprises:

8. The method according to any one of claims 3 to 6, wherein said determining a target acquisition strategy from said target feature declaration data comprises:

if a preset sub-policy comprising an item identifier of the target data item, a data source corresponding to the target data item and an access protocol exists in the preset sub-policy library, the preset sub-policy is used as a sub-policy to which the target data item belongs;

and if the preset sub-strategy library does not contain the item identification of the target data item, the data source corresponding to the target data item and the preset sub-strategy of the access protocol, generating the sub-strategy to which the target data item belongs.

9. The method according to any one of claims 3 to 6, wherein the performing a data acquisition procedure for the target data analysis task according to the target acquisition strategy comprises:

10. The method of claim 9, wherein the collecting data from the different data sources according to the sub-policies included in the target collection policy comprises:

for any sub-policy, establishing connection with a data source of each target data item in the sub-policy according to an access protocol corresponding to the data source;

candidate data corresponding to the data type of each target data item is collected from the data source respectively.

11. The method of claim 10, wherein the establishing a connection with the data source according to the access protocol corresponding to the data source for each of the target data items in the sub-policy comprises:

and establishing connection with the data source by adopting the adapting plug-in.

12. The method according to any one of claims 3 to 6, further comprising:

13. The method according to claim 12, wherein the target feature declaration data further includes data enhancement information corresponding to each target data item required to be collected by the target data analysis task, and the obtaining a target analysis policy according to a collection result of data collection includes:

for each target data item, carrying out data enhancement processing on candidate data corresponding to the target data item in the acquisition result according to the data enhancement information corresponding to the target data item to obtain target data corresponding to the target data item;

and determining the target analysis strategy according to the item identification corresponding to each target data item, the target data and the identification of the target network function NF instance.

14. The method according to claim 12, wherein the method further comprises:

performing data analysis processing according to the target analysis strategy to obtain an analysis result;

and feeding back the analysis result to the consumption network element.

15. The method according to any one of claims 3 to 6, further comprising:

if the item identification and the data type of any target data item in any sub-strategy meet the preset deleting conditions, deleting the item identification and the data type of the target data item in the sub-strategy; the preset deleting condition is used for indicating that the target data item does not belong to the data item required to be acquired by any incomplete data analysis task;

And deleting the sub-strategy if the item identification and the data type of each target data item in any sub-strategy meet the preset deleting conditions.

16. The method according to any one of claims 1 to 6, further comprising:

for each task identifier of the preset data analysis task, determining feature declaration data corresponding to the task identifier according to item identifiers, data types and network element types of a plurality of preset data items corresponding to the task identifier;

and analyzing task identifications of the tasks and feature declaration data corresponding to the task identifications according to the preset data to obtain the feature declaration database.

17. A data processing apparatus, the apparatus comprising:

The first determining module is used for determining a target task identifier of the target data analysis task according to the target request;

the acquisition module is used for inquiring a feature declaration database according to the target task identifier to obtain target feature declaration data corresponding to the target task identifier, wherein a plurality of groups of corresponding relations between the task identifier and the feature declaration data are stored in the feature declaration database, and the target feature declaration data comprise item identifiers of all target data items required to be acquired by the target data analysis task, data types corresponding to all the target data items and acquisition indication information corresponding to all the target data items;

18. An NWDAF network element comprising: a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1-16 when the computer program is executed.

19. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1-16.