KR102441775B1 - How to optimize the network data analysis function device - Google Patents

Abstract

A method for optimizing a network data analysis function device is disclosed. In the optimization method, the network data analysis function device may collect network data according to a request for analysis of network data received from the consumer network function device, and may provide analysis information that is a result of analyzing the network data to the consumer network function device. The network data analysis function device may receive feedback on the analysis information from the consumer network function device, and adjust an analysis method of the network data based on the feedback.

Description

How to optimize the network data analysis function device {OPTIMIZATION FOR NETWORK DATA ANALYTIC DEVICE}

The present invention relates to a method for optimizing a network data analysis function device.

Recently, as various services and low-latency networks are provided, the complexity of network operation is increasing. For example, a network must support slices, support vertical services, and flexible combinations of various services are required. As the complexity of such networks increases, there is a limit to the ability of an existing person to operate the network.

Therefore, a separate network data analysis function device for analyzing network data generated in the network has been proposed. In complex networks, network data is generated in the same form as big data, but a method for efficiently analyzing network data and deriving higher quality analysis information is needed.

The present invention provides a method of optimizing a network data analysis function device that analyzes network data based on a feedback of a network function device that consumes analysis information of the network data.

The present invention improves the performance of the network data analysis function device by evaluating that the network data analysis function device has performed analysis information of network data, and changing the analysis method when analyzing network data based on the evaluation result. provide a way

A method of optimizing a network data analysis function device according to an embodiment of the present invention includes: receiving a network data analysis request message from a consumer network function device that wants to use analysis information of network data; collecting first network data for network analysis based on the analysis request message from a first provider network function device; generating analysis information on the network data by analyzing the collected network data based on a method of analyzing the network data; providing an analysis response message including analysis information of the network data to a consumer network function device; receiving feedback on the analysis information of the network data from the consumer network function device; collecting second network data from a second provider network function device to evaluate the analysis information of the network data; and changing the network data analysis method performed by the network data analysis function device based on at least one of the received feedback and second network data.

The generating of the analysis information may include selecting at least one analysis model from among a plurality of analysis models in order to generate the analysis information of the network data.

In the changing step, an analysis model used when analyzing the network data may be replaced, deleted, updated, additionally trained, or an analysis model may be added.

The changing may include changing at least one of a type of an analysis model used when analyzing the network data, a weight of layers, the number of layers, and an order of layers, or replacing layers.

The changing may include filtering the first network data collected from the first network function device, and the filtering may include at least one of temporal filtering, spatial filtering, application filtering, network filtering, and slice filtering.

The changing may include changing, replacing, adding, or filtering the learning data used when training the analysis model that generates the analysis information of the network data.

The changing may include increasing the number of learning times of the analysis model, changing the type of the analysis model, or changing the properties of the analysis model while maintaining the type of the analysis model.

The feedback may include whether the consumer network function device has used the analysis information of the network data, information about a change in performance of the consumer network function device when the analysis information of the network data is applied, and the analysis information of the network data It may include at least one of satisfaction, a use case for use of the analysis information of the network data, and temporal or spatial information about the use of the network data.

In the receiving of the analysis request message, when there are a plurality of network data analysis devices, the consumer network function device selects at least one network data analysis device for generating analysis information of network data from among network data analysis devices, or Alternatively, the network function storage device may select, and each of the selected network data analysis devices may receive the analysis request message.

The changing of the analysis method includes performing evaluation of the analysis information of the first network data based on the feedback and the second network data, and based on the evaluation of the analysis information of the first network data, the You can change the way network data is analyzed.

A network data analysis function device according to an embodiment of the present invention includes a processor, wherein the processor includes a network data analysis request message from a consumer network function device that wants to use analysis information of network data , collects first network data for network analysis from the first provider network function device based on the analysis request message, and analyzes the collected network data based on a method of analyzing the network data. generates analysis information on the network data, provides an analysis response message including the analysis information of the network data to the consumer network function device, receives feedback on the analysis information of the network data from the consumer network function device, and the network Collecting second network data from a second provider network function device to evaluate analysis information of the data, and performing network data analysis performed by the network data analysis function device based on at least one of the received feedback and second network data analysis method can be changed.

The processor may select at least one analysis model from among a plurality of analysis models to generate the analysis information of the network data.

The processor may change an analysis method of network data by replacing, deleting, updating, additional training, or adding an analysis model used when analyzing the network data.

The processor may change the analysis method of the network data by changing at least one of the type of analysis model used when analyzing the network data, the weight of the layers, the number of layers, and the order of the layers, or by replacing the layers.

The processor may filter the first network data collected from the first network function device, and the filtering may include at least one of temporal filtering, spatial filtering, application filtering, network filtering, and slice filtering.

The processor may change the analysis method of the network data by changing, replacing, adding, or filtering the training data used when training the analysis model that generates the analysis information of the network data.

The processor may increase the number of learning times of the analysis model, change the type of the analysis model, or change the properties of the analysis model while maintaining the type of the analysis model.

The feedback may include whether the consumer network function device has used the analysis information of the network data, information about a change in performance of the consumer network function device when the analysis information of the network data is applied, and the analysis information of the network data It may include at least one of satisfaction, a use case for use of the analysis information of the network data, and temporal or spatial information about the use of the network data.

The processor may be configured to, when the number of the network data analysis apparatuses is plural, the consumer network function apparatus selects at least one network data analysis apparatus for generating analysis information of network data from among the network data analysis apparatuses, or the network function storage apparatus selected, and each of the selected network data analysis devices may receive the analysis request message.

The processor performs evaluation on the analysis information of the first network data based on the feedback and the second network data, and based on the evaluation of the analysis information of the first network data, the analysis method of the network data can be changed for

According to an embodiment of the present invention, it is possible to optimize the network data analysis function device that analyzes the network data based on the feedback of the network function device that consumes the analysis information of the network data.

According to an embodiment of the present invention, a network data analysis function is performed by evaluating that the network data analysis function device performs analysis information of network data, and changing an analysis method when analyzing network data based on the evaluation result. The performance of the device may be improved.

1 is a diagram for explaining the operation of a network data analysis function device according to an embodiment of the present invention.
2 is a flowchart illustrating a method for optimizing a network data analysis function apparatus according to an embodiment of the present invention.
3 is a view for explaining a processing process after receiving feedback on analysis information of a network data analysis function device according to an embodiment of the present invention.
4 is a diagram illustrating a processing process of a network data analysis function device according to an embodiment of the present invention.
FIG. 5 is a diagram illustrating a process for processing a plurality of network data analysis function devices according to an embodiment of the present invention.

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. However, the scope of the patent application is not limited or limited by these embodiments. Like reference numerals in each figure indicate like elements.

Various modifications may be made to the embodiments described below. It should be understood that the embodiments described below are not intended to limit the embodiments, and include all modifications, equivalents, and substitutions thereto.

Terms such as first or second may be used to describe various elements, but these terms should be understood only for the purpose of distinguishing one element from another element. For example, a first component may be termed a second component, and similarly, a second component may also be termed a first component.

Terms used in the examples are only used to describe specific examples, and are not intended to limit the examples. The singular expression includes the plural expression unless the context clearly dictates otherwise. In this specification, terms such as "comprises" or "have" are intended to designate that the features, numbers, steps, operations, components, parts, or combinations thereof described in the specification exist, but one or more other features It is to be understood that this does not preclude the possibility of the presence or addition of numbers, steps, operations, components, parts, or combinations thereof.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which the embodiment belongs. Terms such as those defined in a commonly used dictionary should be interpreted as having a meaning consistent with the meaning in the context of the related art, and should not be interpreted in an ideal or excessively formal meaning unless explicitly defined in the present application. does not

In addition, in the description with reference to the accompanying drawings, the same components are assigned the same reference numerals regardless of the reference numerals, and the overlapping description thereof will be omitted. In the description of the embodiment, if it is determined that a detailed description of a related known technology may unnecessarily obscure the gist of the embodiment, the detailed description thereof will be omitted.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 is a diagram for explaining the operation of a network data analysis function device according to an embodiment of the present invention.

1, the network data analysis function device (Network Data Analytics Function: NWDAF) 101 is a consumer network function device (Consumer Network Function) 102 and at least one provider network function device (Provider Network Function) to It may be connected to the corresponding first provider network function device 103 - 1 , the second provider network function device 103 - 2 , and the network storage function device 104 . Also, although not shown in FIG. 1 , the network data analysis function device 101 may be connected to an OAM function device (Operations, administration and management) 105 .

The network data analysis function device 101 may receive an analysis request (or analysis subscription) for network data from the consumer network function device 102 . The consumer network function device 102 refers to a network function device that intends to use analysis information on network data. Then, the network data analysis function device 101 may collect the first network data for analysis from the first provider network function device 103 - 1 based on the analysis request for the network data.

The network data analysis function device 101 may analyze the first network data collected from the first provider network function device 103 - 1 . The first provider network function device 103 - 1 may refer to a network function device that provides first network data necessary to generate analysis information of network data. The network data analysis function device 101 transmits the analysis information of the first network data collected from the first provider network function device 103-1 in response to the analysis request for the first network data to the consumer network function device 102 can be provided to In addition, the consumer network function device 102 may provide feedback on the analysis information of the first network data to the network data analysis function device 101 .

The network data analysis function device 101 may collect the second network data from the second provider network function device 103 - 2 to evaluate the analysis information of the first network data. The second provider network function device 103 - 2 may refer to a network function device that provides second network data necessary to evaluate the analysis information of the network data.

In this case, the first provider network function device 103-1 may be the same as or different from the second provider network function device 103-2. Also, the first network data may be the same as or different from the second network data.

The network data analysis function device 101 may evaluate the analysis information of the first network data by using the second network data. In addition, the network data analysis function device 101 may change the analysis method of the first network data based on the evaluation of the analysis information of the first network data.

The operation of the network data analysis function device 101 will be described in more detail with reference to FIGS. 2 to 5 .

2 is a flowchart illustrating a method for optimizing a network data analysis function apparatus according to an embodiment of the present invention.

In step (i), the consumer network function device 102 may transmit a network data analysis request to the network data analysis function device 101 . In this case, the consumer network function device 102 may transmit an analysis request message of network data (eg Nnwdaf_AnalyticsInfo_Request) or an analysis subscription message of network data (eg. Nnwdaf_AnalyticsSubscription_Subscribe) to the network data analysis function device 101 .

The analysis request message of network data or the analysis subscription message of network data may include a type of consumer network function device (eg, AMF or SMF, etc.) and a use case indication. Alternatively, the analysis request message of network data or the analysis subscription message of network data may further include analytics filter information.

Here, the type is information for distinguishing what type of network function device the consumer network function device is. In addition, the use case indication is information indicating a plurality of use cases. In one example, the use case indication identifies a purpose for analytics of network data requested by the consumer network function device 102 .

In step (ii), the network data analysis function device 101 may collect the first network data from the provider network function device 103 or the OAM device 105 . Then, the network data analysis function device 101 generates analysis information on the first network data by performing analysis on the first network data collected in response to a request for analysis of the network data received from the consumer network function device 102 . can

In this case, the network data analysis function device 101 may identify an analysis model that generates analysis information for the first network data. For example, the network data analysis function device 101 may generate an analysis model itself or call an analysis model generated by another entity.

As an example, the analytics model may include a target of analytics reporting, analytics reporting parameters, analytics filter information, network function device type (NF Type), or use case indication. It may be determined based on at least one.

In this case, the target of the analysis reporting may mean a user terminal or a group of user terminals. In addition, the analysis reporting parameter may include a timestamp for the first network data collected by the network data analysis function device 101, a collection period for the first network data, and the like. The analysis filter information may include the location of the user terminal, slice information used by the user terminal, and the like. And, the type of the network function device may mean information for classifying the type of the consumer network function device 102 . Also, the use case indication may mean information indicating a plurality of use cases.

In step (iii), the network data analysis function device 101 needs to obtain feedback from the consumer network function device 102 in order to evaluate the analysis model for a specific use case or the consumer network function device 102 . . Then, the network data analysis function device 101 may provide the analysis information of the first network data to the consumer network function device 102 in response to the network data analysis request received from the consumer network function device 102 .

In this case, the response to the network data analysis request may include a response message to the network data analysis request (eg Nnwdaf_AnalyticsInfo_Request_response) or a notification message for network data analysis subscription (Nnwdaf_AnalyticsSubscription_Notify).

The response message to the request for analysis of network data or the notification message for subscription to analysis of network data may include a feedback indication or an expiration time. The feedback indication is information identifying whether it is necessary to receive feedback on the analysis information of the first network data from the consumer network function device 102 . and the expiration time identifies an expiration time for obtaining feedback.

In step (iv), the consumer network function device 102 may receive analysis information on the first network data from the network data analysis function device 101 . In addition, when a feedback indication is enabled in a response message to a request for analysis of network data including analysis information for the first network data or a notification message for an analysis subscription of network data, the consumer network function device ( 102 may provide feedback on the analysis information of the first network data to the network analysis function device 101 . In this case, the consumer network function device 102 may provide feedback on the analysis information of the network data to the network data analysis device 101 through a feedback message (eg, Nnwdaf_AnalyticsInfo_Feedback or Nnwdaf_AnalyticsSubscription_Feedback).

Here, the feedback message is an analysis information ID (Analytics ID), whether analysis information is used (Analytics Usage), a type of consumer network functional device (NF Type), a use case indication (Use Case Indication), an evaluation value (Evaluation value) , a Notification Target Address (+ Notification Correlation Id), a timestamp for feedback, and the like.

The analysis information ID is information indicating analysis information related to feedback. Whether the analysis information is used is information for identifying whether the consumer network function device 102 uses the analysis information for the first network data. Whether to use the analysis information may be enabled when the consumer network function device 102 performs one or a plurality of actions according to the analysis information.

The type of consumer network function device is information for identifying what kind of network function device (eg, AMF or SMF) the consumer network function device 102 is. The use case indication is information for identifying the purpose of the action performed by the consumer network function device 102 according to the analysis information on the first network data. The use case indication indicates a plurality of use cases.

According to an embodiment of the present invention, the use case indication described in step (i) and the use case indication described in step (iv) may be different. This is because the consumer network function device 102 does not perform an action on the use case indicated by the use case indication described in step (i).

The evaluation value indicates satisfaction with the analysis information of the first network data obtained by the consumer network function device 102 from the network data analysis function device 101 . The evaluation value is provided when the consumer network function device 102 evaluates the analysis information of the first network data.

The notification target address and notification correlation information are information at the time of subscribing to analysis of network data. The notification target address indicates the address of the consumer network function device. The notification correlation ID is information for correlating notifications from the network data analysis function device 101 to the consumer network function device 102 when a subscription is applied. The timestamp for the feedback means the point in time when the consumer network function device generates the feedback.

In step (v), the network data analysis function device 101 may collect the second network data from the provider network function device 103 or the OAM device 105 . The first network data may be the same as or different from the second network data. The provider network function device 103 described in step (ii) may correspond to the first provider network function device 103-1 in FIG. 1, and the provider network function device 103 described in step (v) ) may correspond to the second provider network function device 103 - 2 of FIG. 1 .

In step (vi), the network data analysis function device 101 evaluates the analysis information of the first network data based on the feedback obtained from the consumer network function device 102 and the second network data collected in step (v). can In addition, the network data analysis function device 101 may change the analysis method used when generating the analysis information of the first network data for a specific use case or a specific network function device based on the evaluation result. For example, the network data analysis function device 101 may update an analysis model used when generating analysis information of the first network data (eg, optimize or additionally train the analysis model).

3 is a view for explaining a processing process after receiving feedback on analysis information of a network data analysis function device according to an embodiment of the present invention.

Referring to FIG. 3 , the network data analysis function device 101 may receive a network data analysis request from the consumer network function device 102 . Then, the network data analysis function device 101 may collect network data from the provider network function device 103 in response to the network data analysis request. In addition, the network data analysis function device 101 may select at least one of the plurality of analysis models (analysis model 1 - analysis model N) and analyze the collected network data as the selected analysis model. The network data analysis function device 101 may generate analysis information of the network data by analyzing the network data using the selected analysis model.

According to an embodiment of the present invention, the network data analysis function device 101 may use a plurality of analysis models. And, each of the analysis models may be optimized for a particular use of the consumer network function device 102 . The network data analysis function device 101 is based on information (eg, analysis reporting target, analysis filter, etc.) included in the network data analysis request transmitted by the consumer network function device 101 among a plurality of analysis models. Thus, an appropriate analytical model can be selected.

Multiple analysis models may be essential to support different use cases for the same analysis information. For example, the requirements for the analysis model for the same analysis ID transmitted by the consumer network function device 102 may be different for each use case. For example, in certain use cases, the processing delay that occurs when generating analysis information may be relatively more important than the accuracy level, and in other use cases, the accuracy level may be relatively more important than the processing delay. .

So, according to an embodiment of the present invention, a plurality of analysis models may be supported. The network data analysis function device 101 may provide appropriate analysis information from an analysis model optimized for a use case for analysis information labeled with the same analysis ID.

According to an embodiment of the present invention, the network data analysis function device 101 provides information (eg, an analysis request message for network data or an analysis subscription message for network data transmitted from the consumer network function device 102 ). , analysis reporting target, analysis reporting parameters, analysis filter information, network function device type, use case indication, etc.) can be categorized. The network data analysis function device 101 may recognize the use case of the network data analysis request according to the categorized result.

In addition, according to an embodiment of the present invention, a network is performed using network data collected from the second network function devices 103 - 2 or the OAM device 105 as well as the feedback received from the consumer network function device 102 . Evaluation may be performed on the analysis information generated by the data analysis function device 101 .

And, according to an embodiment of the present invention, adjustment (eg, optimization or additional model training) may be performed on the analysis model that generates the analysis information based on the evaluation. Accordingly, the network data analysis function device 101 can provide analysis information more appropriate for a specific use in the consumer network function device 102 .

As an example, the analysis information of network data includes (i) slice load level information at the network slice instance level, (ii) observed service experience (ex. service experience for network slices, service experience for the application), (iii) load information of the network function device (ex. load statistics information or load prediction information for the network function device), (iv) network performance information (ex. network performance) (statistical information or prediction information about prediction information), predicted behavior of user terminal, non-ideal behavior of user terminal, etc.), (vi) congestion level information of user data (statistical information, prediction information), (vii) QoS continuity information (statistical information, prediction information) can be identified by an analysis ID representing, etc. For the above-mentioned analysis information, the format and contents of network data to be collected by the network data analysis function device 101 may be different, and the contents of the analysis information may also be different.

Then, the network data analysis function device 101 may provide the analysis information of the network data to the consumer network function device 102 . In this case, the consumer network function device 102 may provide a feedback on the analysis information of the network data to the network data analysis function device 101 . According to an embodiment of the present invention, when the feedback indication is enabled, the consumer network function device 102 may provide feedback on the analysis information of the network data to the network data analysis function device 101 . According to another embodiment of the present invention, regardless of the feedback indication, whenever the consumer network function device 102 receives the analysis information of the network data from the network data analysis function device 101, the feedback on the analysis information is provided to the network data. It can be provided to the analysis function device 101 .

The network data analysis function device 101 may change the analysis method of the network data based on the feedback provided by the consumer network function device 102 . According to an embodiment of the present invention, the network data analysis function device 101 may analyze network data by selecting at least one analysis model from among a plurality of analysis models trained through machine learning. In this case, the analysis model may be a neural network, and various types of neural networks such as CNN, DNN, and SVM may be used. At this time, the analysis model may be trained by the network data function device 101 or by an entity different from the network data function device 101 .

According to an embodiment of the present invention, changing the network data analysis method may mean additionally training the analysis model used by the network data analysis function device 101 to analyze the network data. In this case, as the evaluation value in the feedback of the network data is lower, the number of additional training of the analysis model may increase.

According to an embodiment of the present invention, changing the analysis method of network data may include changing an analysis model used by the network data analysis function device 101 to analyze network data to another analysis model, or analyzing network data thereafter. To do this, an analysis model may be added, or at least some or all of the selected plurality of analysis models may be replaced. Accordingly, an analysis model used when analyzing network data may be improved, and an analysis method may be updated.

DNN), 분석 모델의 종류는 유지하면서 분석 모델을 구성하는 레이어의 개수를 증가, 레이어를 교체하거나 또는 레이어별 특징값을 변경하는 것을 의미할 수 있다.According to an embodiment of the present invention, changing the analysis method of network data may change the type of analysis model used when analyzing network data (ex. CNN)

DNN), may mean increasing the number of layers constituting the analysis model while maintaining the type of analysis model, replacing layers, or changing feature values for each layer.

According to an embodiment of the present invention, changing the analysis method of network data may mean changing, replacing, or adding the provider network function device 103 that provides network data. Alternatively, according to an embodiment of the present invention, changing the analysis method of network data does not use all of the network data collected from the provider network function device 103 as it is but filtering (eg, temporal filtering - acquiring at a specific time or Alternatively, it may mean using network data to which analysis using only network data generated at a specific time or spatial filtering-analyzing using only network data acquired at a specific location or generated at a specific location) is applied. Alternatively, according to an embodiment of the present invention, changing the network data analysis method may include changing the type, attribute (format, metadata, size, etc.), quantity, etc. of network data collected from the provider network function device 103 . It could mean change.

According to an embodiment of the present invention, changing the analysis method of network data may mean changing/replacing the learning data used when training the analysis model. Alternatively, according to another embodiment of the present invention, changing the analysis method of network data may include adding or filtering the learning data used when training the analysis model (eg, temporal filtering (learning generated by the user terminal in a specific time period) Data only), spatial filtering (using only training data generated in a specific place), application filtering (using only training data generated by a specific application used in the user terminal), network filtering (user terminal accessing a specific network or cell) training data generated when the user terminal is used) and slice filtering (learning data generated when a specific slice is assigned to the user terminal) can be performed.

According to one embodiment of the present invention, when the network data analysis function device 101 receives an analysis subscription rather than a network data analysis request from the consumer network function device 102, changing the analysis method of the network data is previously It may mean changing the collection method for network data in one cycle in the next cycle. Here, a method of collecting network data may include changing a temporal range, a spatial range, or a collection source.

Feedback on the analysis information may be provided to the entity training the analysis model. For example, when the network data analysis function device 101 trains the analysis model by itself, feedback on the analysis information provided by the consumer network function device 102 may be provided to the network data analysis function device 101 . . However, when the analysis model is trained in the network storage function device 104 connected to the network data analysis function device 101, feedback on the analysis information provided by the consumer network function device 102 is the network storage function device ( 104) can be provided.

For example, the feedback may include information on whether the consumer network function device 102 has used the analysis information of the network data, and information on the performance change of the consumer network function device when the analysis information of the network data is applied (eg, processing speed) , accuracy, and the like), satisfaction with analysis information of network data, usage purpose of analysis information of network data, and temporal or spatial information about use of network data may be included.

The network data analysis function device 101 may analyze the network data to generate analysis information of the network data. At this time, the network data analysis function device 101 provides the network data analysis information to the consumer network function device 102 without self-evaluating the analysis information, or after self-evaluation, only when the quality of the network data is higher than a certain level. It can be provided to the network function device 102 . If the analysis information generated by the network data analysis function device 101 does not indicate a quality above a certain level, the network data analysis function device 101 provides the above-mentioned analysis information to the consumer network function device 102 . It is possible to change the analysis method of one network data.

4 is a diagram illustrating a processing process of a network data analysis function device according to an embodiment of the present invention.

Referring to FIG. 4 , in step (1), the consumer network function device 102 may transmit a network data analysis request to the network data analysis function device 101 . In step (2), the network data analysis function device 101 may collect first network data from the first provider network function device 103 - 1 . Here, the first network data may mean network data used for analysis of the network data.

In step (3), the network data analysis function device 101 may analyze the first network data collected from the first provider network function device 103-1 to generate analysis information of the first network data. . Then, the network data analysis function device 101 may provide the analysis information of the first network data to the consumer network function device 102 that has transmitted the network data analysis request.

In step (4), the consumer network function device 102 may use the analysis information obtained from the network data analysis function device 101 . In addition, the consumer network function device 102 may provide feedback on the analysis information to the network data function device 101 .

In step 5 , the network data analysis function device 101 may collect second network data from the second provider network function device 103 - 2 . The second network data may refer to network data for evaluating analysis information of the first network data.

In step (6), the network data analysis function device 101 may self-evaluate the analysis information of the first network data using the feedback and the second network data obtained from the consumer network function device 102 . In addition, the network data analysis function device 101 may change the analysis method of the first network data based on the evaluation information evaluated by itself on the analysis information of the first network data.

FIG. 5 is a diagram illustrating a process for processing a plurality of network data analysis function devices according to an embodiment of the present invention.

Referring to FIG. 5 , a case in which there are N network data analysis function devices will be described. The consumer network function device 102 may select any one of the N network data analysis function devices 101-1 to 101-N to transmit a network data analysis request to use the analysis information of the network data. . At this time, the consumer network function device 102 obtains a list of N network data analysis function devices 101-1 to 101-N from the network storage function device 104, and is suitable for the network data analysis request. At least one network data analysis function device may be selected. Alternatively, the consumer network function device 102 may check the network storage function device 104 by inquiring the network data analysis device suitable for the network data analysis request. The network storage function device 104 may store addresses and profiles for the network function device. Here, the profile of the network function device may mean the type and type of the network function device.

Alternatively, the consumer network function device 102 may request network data analysis from different network data analysis devices for each analysis of the network data. For example, when requesting the analysis information A of network data, the consumer network function device 102 may request the analysis information of the network data from the network data analysis function device 101-1. In addition, when requesting the analysis information B of the network data, the consumer network function device 102 may request the analysis information of the network data from the network data analysis function device 101 - 2 .

As an example, the consumer network function device 102 may request the same analysis information from a plurality of network data function analysis devices in order to request analysis information of the same network data. In addition, the consumer network function device 102 may use the analysis information after obtaining all analysis information from the plurality of network data function analysis devices. Alternatively, after the consumer network function device 102 obtains all analysis information from a plurality of network data function analysis devices, at least one analysis information according to a specific criterion (accuracy, preference, time, space, application) You can choose to use it.

Meanwhile, the method according to the present invention is written as a program that can be executed on a computer and can be implemented in various recording media such as magnetic storage media, optical reading media, and digital storage media.

Implementations of the various techniques described herein may be implemented in digital electronic circuitry, or in computer hardware, firmware, software, or combinations thereof. Implementations may be implemented for processing by, or for controlling the operation of, a data processing functional device, eg a programmable processor, computer, or multiple computers, a computer program product, ie an information carrier, eg a machine readable It may be implemented as a computer program tangibly embodied in a storage function device (computer readable medium) or a radio signal. A computer program, such as the computer program(s) described above, may be written in any form of programming language, including compiled or interpreted languages, and may be written as a standalone program or in a module, component, subroutine, or computing environment. It can be deployed in any form, including as other units suitable for use in A computer program may be deployed to be processed on one computer or multiple computers at one site or to be distributed across multiple sites and interconnected by a communications network.

Processors suitable for processing a computer program include, by way of example, both general and special purpose microprocessors, and any one or more processors of any kind of digital computer. Generally, a processor will receive instructions and data from either read-only memory or random access memory or both. Elements of a computer may include at least one processor for executing instructions and one or more memory functional devices for storing instructions and data. Generally, a computer may include one or more mass storage functional devices for storing data, for example magnetic, magneto-optical disks, or optical disks, receiving data from, sending data to, or receiving data therefrom. It may be combined so as to be both sides. Information carriers suitable for embodying computer program instructions and data are, for example, semiconductor memory functional devices, for example, magnetic media such as hard disks, floppy disks and magnetic tapes, Compact Disk Read Only (CD-ROM). Memory), optical recording media such as DVD (Digital Video Disk), magneto-optical media such as optical disk, ROM (Read Only Memory), RAM ( RAM, Random Access Memory), flash memory, EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), and the like. Processors and memories may be supplemented by, or included in, special purpose logic circuitry.

In addition, the computer-readable medium may be any available medium that can be accessed by a computer, and may include both computer storage media and transmission media.

While this specification contains numerous specific implementation details, these should not be construed as limitations on the scope of any invention or claim, but rather as descriptions of features that may be specific to particular embodiments of particular inventions. should be understood Certain features that are described herein in the context of separate embodiments may be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment may also be implemented in multiple embodiments, either individually or in any suitable subcombination. Furthermore, although features operate in a particular combination and may be initially depicted as claimed as such, one or more features from a claimed combination may in some cases be excluded from the combination, the claimed combination being a sub-combination. or a variant of a sub-combination.

Likewise, although acts are depicted in the figures in a particular order, it should not be understood that such acts must be performed in the specific order or sequential order shown or that all depicted acts must be performed in order to obtain desirable results. In certain cases, multitasking and parallel processing may be advantageous. In addition, the separation of the various functional device components of the above-described embodiments should not be construed as requiring such separation in all embodiments, and the described program components and functional devices are generally integrated together into a single software product or in multiple software products. It should be understood that it can be packaged.

On the other hand, the embodiments of the present invention disclosed in the present specification and drawings are merely presented as specific examples to aid understanding, and are not intended to limit the scope of the present invention. It will be apparent to those of ordinary skill in the art to which the present invention pertains that other modifications based on the technical spirit of the present invention can be implemented in addition to the embodiments disclosed herein.

Claims (20)

A method for optimizing a network data analysis function device, the method comprising:
Receiving an analysis request message or an analysis subscription message of network data from a consumer network function device that wants to use analysis information of network data - The analysis request message or analysis subscription message is a type of a consumer network function device, a use case contains indication or analysis filter information;
collecting first network data for network analysis based on the analysis request message or the analysis subscription message from a first provider network function device;
generating analysis information on the network data by analyzing the collected network data based on a method of analyzing the network data;
providing an analysis response message or analysis notification message including analysis information of the network data to a consumer network function device, wherein the analysis response message or analysis notification message is a feedback indication or an expiration time (Expiry Time) including; and
Receiving feedback on the analysis information of the network data from the consumer network function device
A method of optimizing a network data analysis function device comprising a. According to claim 1,
The network data analysis function device optimizes the network data analysis function device to generate analysis information by using an analysis model selected based on a target of analysis reporting or an analysis filter. According to claim 1,
collecting second network data from a second provider network function device to evaluate analysis information of the network data; and
changing the network data analysis method performed by the network data analysis function device based on at least one of the feedback and the second network data;
The optimization method of the network data analysis function device further comprising a. 4. The method of claim 3,
The changing step is
A method of optimizing a network data analysis function device for changing or replacing at least one of a type of an analysis model used when analyzing the network data, a weight of layers, the number of layers, and an order of layers. 4. The method of claim 3,
The changing step is
filtering the first network data collected from the first network function device;
The filtering may include at least one of temporal filtering, spatial filtering, application filtering, network filtering, and slice filtering. 4. The method of claim 3,
The changing step is
A method of optimizing a network data analysis function device for changing, replacing, adding, or filtering the training data used when training the analysis model that generates the analysis information of the network data. 4. The method of claim 3,
The changing step is
A network data analysis function device for increasing the number of learning times of the analysis model generating the analysis information of the network data, changing the type of the analysis model, or changing the properties of the analysis model while maintaining the type of the analysis model Optimization method. According to claim 1,
The feedback is
Whether the consumer network function device uses the analysis information of the network data, information on a change in the performance of the consumer network function device when the analysis information of the network data is applied, satisfaction with the analysis information of the network data, the network A method of optimizing a network data analysis function device comprising at least one of a use case for use of the analysis information of data, and temporal or spatial information on the use of the network data. According to claim 1,
Receiving the analysis request message comprises:
When there are a plurality of network data analysis devices, the consumer network function device selects at least one network data analysis device that generates analysis information of network data from among the network data analysis devices, or the network function storage device selects, and A method for optimizing a network data analysis function device in which each of the selected network data analysis devices receives the analysis request message. delete A network data analysis function device comprising:
The network data analysis function device includes a processor,
The processor is
Receive an analysis request message or analysis subscription message of network data from a consumer network function device that wants to use analysis information of network data; The analysis request message or analysis subscription message includes a type of consumer network function device, use case indication, or analysis filter information;
collect first network data for network analysis based on the analysis request message or analysis subscription message from the first provider network function device;
By analyzing the collected network data based on the method of analyzing the network data, analysis information for the network data is generated,
providing an analysis response message or analysis notification message including analysis information of the network data to a consumer network function device; The analysis response message or analysis notification message includes a feedback indication (Feedback Indication) or an expiration time (Expiry Time)-;
A network data analysis function device for receiving a feedback on the analysis information of the network data from the consumer network function device. 12. The method of claim 11,
The processor is
A network data analysis function device for generating analysis information using an analysis model selected based on a target of analysis reporting or an analysis filter. 12. The method of claim 11,
The processor is
collect second network data from a second provider network function device to evaluate the analysis information of the network data;
A network data analysis function device for changing a network data analysis method performed by the network data analysis function device based on at least one of the feedback and second network data. 14. The method of claim 13,
The processor is
A network data analysis function device for changing an analysis method of network data by changing at least one of a type of analysis model used when analyzing the network data, weight of layers, number of layers, and order of layers, or by replacing layers. 14. The method of claim 13,
The processor is
filtering the first network data collected from the first network function device;
The filtering may include at least one of temporal filtering, spatial filtering, application filtering, network filtering, and slice filtering. 14. The method of claim 13,
The processor is
A network data analysis function device for changing an analysis method of network data by changing, replacing, adding, or filtering the training data used when training the analysis model that generates the analysis information of the network data. 12. The method of claim 11,
The processor is
A network data analysis function device for increasing the number of learning times of the analysis model generating the analysis information of the network data, changing the type of the analysis model, or changing the properties of the analysis model while maintaining the type of the analysis model. 12. The method of claim 11,
The feedback is
Whether the consumer network function device uses the analysis information of the network data, information on a change in the performance of the consumer network function device when the analysis information of the network data is applied, satisfaction with the analysis information of the network data, the network A network data analysis function device comprising at least one of a use case for use of the analysis information of data, and temporal or spatial information about the use of the network data. 12. The method of claim 11,
The processor is
When there are a plurality of network data analysis devices, the consumer network function device selects at least one network data analysis device that generates analysis information of network data from among the network data analysis devices, or the network function storage device selects, and A network data analysis function device in which each of the selected network data analysis devices receives the analysis request message. 12. The method of claim 11,
The processor is
Evaluate the analysis information of the first network data based on the feedback and the second network data,
A network data analysis function device for changing an analysis method of the network data based on the evaluation of the analysis information of the first network data.

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