CN113572584B - Network data analysis method, functional entity and system - Google Patents
Network data analysis method, functional entity and system Download PDFInfo
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- CN113572584B CN113572584B CN202010353684.9A CN202010353684A CN113572584B CN 113572584 B CN113572584 B CN 113572584B CN 202010353684 A CN202010353684 A CN 202010353684A CN 113572584 B CN113572584 B CN 113572584B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L5/00—Arrangements affording multiple use of the transmission path
- H04L5/003—Arrangements for allocating sub-channels of the transmission path
- H04L5/0078—Timing of allocation
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W8/00—Network data management
- H04W8/18—Processing of user or subscriber data, e.g. subscribed services, user preferences or user profiles; Transfer of user or subscriber data
Abstract
The disclosure provides a method, a functional entity and a system for network data analysis, and relates to the field of communication. The NWDAF entity fully analyzes the acquired network data based on the configured whole analysis time interval of each analysis task, and sends the analysis result of the current time to the network entity subscribing the analysis task under the condition that the interval between the current time and the time for sending the analysis result of the analysis task last time is equal to or larger than the configured analysis time interval of the analysis task, so that the analysis cycle problem occurring in the network data analysis is improved, the running stability of the system is improved, the NWDAF entity obtains the analysis result based on the relatively stable system state, and the analysis effectiveness is improved.
Description
Technical Field
The present disclosure relates to the field of communications, and in particular, to a method, a functional entity, and a system for network data analysis.
Background
In a fifth Generation (5th Generation) mobile communication system, a Network Data analysis Function (NWDAF) entity is introduced to perform Network Data analysis.
In some cases, the NWDAF entity acquires and analyzes data from a plurality of first network entities, and the second network entity acquires an analysis result from the NWDAF entity, so that when policy adjustment is performed according to the analysis result, data changes of the plurality of first network entities are caused, and the data changes trigger the NWDAF entity to analyze again and update the analysis result, thereby causing an analysis cycle which cannot be stopped and affecting the stability of system operation.
Disclosure of Invention
In the embodiment of the present disclosure, the NWDAF entity fully analyzes the acquired network data for each analysis task based on the configured entire analysis time interval of the analysis task, and in a case that an interval between the current time and the time of sending out the analysis result of the analysis task last time is equal to or greater than the configured analysis time interval of the analysis task, for example, in a case of an integral multiple of the analysis time interval, sends the analysis result of this time to a network entity subscribing to the analysis task, thereby improving an analysis cycle problem occurring in the network data analysis, improving the stability of system operation, enabling the NWDAF entity to obtain the analysis result based on a relatively stable system state, and improving the effectiveness of analysis.
Some embodiments of the present disclosure provide a method for network data analysis, including: the network data analysis function NWDAF entity analyzes the collected network data for each analysis task based on the configured analysis time interval of the analysis task; and the NWDAF entity sends the analysis result of the current time to a network entity subscribing the analysis task under the condition that the interval between the current time and the time for sending the analysis result of the analysis task last time is equal to or more than the configured analysis time interval of the analysis task.
In some embodiments, the NWDAF entity sends the analysis result of the current time to the network entity subscribing to the analysis task when an interval between the current time and a time at which the analysis result of the analysis task was sent last time is an integer multiple of an analysis time interval.
In some embodiments, the analysis time interval of each analysis task is configured as one or more meta-analysis time intervals.
In some embodiments, further comprising: the length of the analysis time interval of all analysis tasks is configured or adjusted by configuring or adjusting the length of the meta-analysis time interval.
In some embodiments, further comprising: and configuring or adjusting the length of the analysis time interval of each analysis task by configuring or adjusting the number of the meta-analysis time intervals corresponding to each analysis task.
In some embodiments, the number of meta-analysis time intervals corresponding to different analysis tasks is the same or different.
In some embodiments, the length of the analysis time interval or the length of the meta-analysis time interval of each analysis task is configured or adjusted by the NWDAF entity or the core network element.
In some embodiments, the length of the analysis time interval for each analysis task is configured or adjusted by the NWDAF entity or the core network element within a time range provided by the network entity subscribing to the analysis task.
In some embodiments, the length of the analysis time interval of each analysis task is configured or adjusted by the NWDAF entity or the core network element according to one or more of a collection time length of network data required for executing the analysis task, a size of a data volume, a transmission delay, and a processing delay for executing the analysis task.
In some embodiments, the length of the analysis time interval of each analysis task is configured or adjusted by the NWDAF entity or the core network element to be less than or equal to a preset value or less than or equal to a preset reporting period according to the type of the analysis task.
Some embodiments of the present disclosure provide a network data analysis function NWDAF entity, including: a memory; and a processor coupled to the memory, the processor configured to perform the method of network data analysis of any of the embodiments based on instructions stored in the memory.
Some embodiments of the present disclosure provide a network data analysis system, including: a network data analysis function, NWDAF, entity as described in any one of the embodiments; and a network entity subscribing the analysis task, configured to send a subscription request of the analysis task to the NWDAF entity, and receive an analysis result returned by the NWDAF entity.
In some embodiments, further comprising: a core network element configured to configure or adjust a length of an analysis time interval or a length of a meta-analysis time interval of each analysis task.
Some embodiments of the present disclosure propose a non-transitory computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method of network data analysis described in any of the embodiments.
Drawings
The drawings that will be used in the description of the embodiments or the related art will be briefly described below. The present disclosure can be understood more clearly from the following detailed description, which proceeds with reference to the accompanying drawings.
It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without undue inventive faculty.
Fig. 1 illustrates a flow diagram of a method of network data analysis in accordance with some embodiments of the present disclosure.
Fig. 2 shows a flow diagram of a method of network data analysis according to further embodiments of the present disclosure.
Fig. 3 is a schematic diagram of an NWDAF entity of some embodiments of the present disclosure.
Fig. 4 is a schematic diagram of a network data analysis system according to some embodiments of the present disclosure.
Detailed Description
The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure.
Fig. 1 illustrates a flow diagram of a method of network data analysis in accordance with some embodiments of the present disclosure.
As shown in fig. 1, the method of this embodiment includes:
in step 110, the NWDAF entity analyzes the collected network data for each analysis task based on the configured analysis time interval of the analysis task in response to a subscription analysis task request issued by a certain network entity.
The NWDAF entity collects network data from network entities related to an analysis task, and performs sufficient analysis in at least one analysis time interval, for example, performs multiple analyses based on the network data collected multiple times, or performs analysis first and then waits based on the collected network data, or waits first and then performs analysis based on the newly collected network data, and a specific analysis manner may be determined according to the analysis task, and this embodiment does not limit the specific analysis manner based on the analysis time interval.
In step 120, the NWDAF entity sends the current analysis result to the network entity subscribing to the analysis task when the interval between the current time and the time of sending the analysis result of the analysis task last time is equal to or greater than the configured analysis time interval of the analysis task.
For example, when the interval between the current time and the time of sending the analysis result of the analysis task last time is an integer multiple of the analysis time interval, the NWDAF entity sends the analysis result of this time to the network entity subscribing to the analysis task.
The NWDAF entity fully analyzes the collected network data for each analysis task based on the configured whole analysis time interval of the analysis task, and sends the analysis result of this time to the network entity subscribing the analysis task under the condition that the interval between the current time and the time of sending the analysis result of the analysis task last time is equal to or greater than the configured analysis time interval of the analysis task, for example, the interval between the current time and the time of sending the analysis result of the analysis task last time is an integral multiple of the analysis time interval, so as to improve the analysis cycle problem occurring in the analysis of the network data, improve the stability of the system operation, enable the NWDAF entity to obtain the analysis result based on a relatively stable system state, and improve the effectiveness of the analysis.
In some embodiments, the analysis time intervals of the analysis tasks are configured based on meta-analysis time intervals, i.e. the analysis time interval of each analysis task is configured as one or more meta-analysis time intervals. The number of meta-analysis time intervals corresponding to different analysis tasks may be the same or different, and may be determined according to the specific analysis task.
For example, there are two analysis tasks W1 and W2 under the NWDAF entity, and the analysis time interval T1 of the analysis task W1 is n1 meta-analysis time intervals T0, and the formula is: t1 ═ n1 × T0, analysis time interval T2 of analysis task W2 is n2 meta-analysis time intervals T0, and the formula is: t2 ═ n2 × T0, and n1 and n2 may be the same or different.
Therefore, the minimum time granularity of the analysis time intervals configured for all the analysis tasks is uniform, and adjustment of the time intervals for a single analysis task and for all the analysis tasks is facilitated, which is specifically described below.
In some embodiments, the length of the analysis time interval for all analysis tasks is configured or adjusted by configuring or adjusting the length of the meta-analysis time interval. For example, before the analysis, the length of the meta-analysis time interval is configured, and in the analysis process, the length of the meta-analysis time interval is adjusted.
For example, there are two analysis tasks W1 and W2 under the NWDAF entity, and the analysis time interval T1 of the analysis task W1 is n1 meta-analysis time intervals T0, and the formula is: t1 ═ n1 × T0, analysis time interval T2 of analysis task W2 is n2 meta-analysis time intervals T0, and the formula is: t2 — n2 × T0, the lengths of the analysis time intervals T1 and T2 of the analysis tasks W1 and W2 are changed by adjusting the length of the meta-analysis time interval T0.
In some embodiments, the length of the analysis time interval of an analysis task is configured or adjusted by configuring or adjusting the number of meta-analysis time intervals corresponding to each analysis task. For example, before the analysis, the number of meta-analysis time intervals corresponding to the analysis task is configured, and in the analysis process, the number of meta-analysis time intervals corresponding to the analysis task is adjusted.
For example, there are two analysis tasks W1 and W2 under the NWDAF entity, and the analysis time interval T1 of the analysis task W1 is n1 meta-analysis time intervals T0, and the formula is: t1 ═ n1 × T0, analysis time interval T2 of analysis task W2 is n2 meta-analysis time intervals T0, and the formula is: t2 is n2 × T0, and the length of analysis time interval T1 of analysis task W1 is changed by adjusting the size of n1, and the length of analysis time interval T2 of analysis task W2 is changed by adjusting the size of n 2.
In some embodiments, the length of the analysis time interval or the length of the meta-analysis time interval for each analysis task is configured or adjusted by the NWDAF entity or the core network element. The NWDAF entity or the core network element may determine the length of the meta-analysis time interval according to the processing performance of the NWDAF entity, and the stronger the processing performance is, the smaller the length of the meta-analysis time interval is. The Core network element may be, for example, an AMF (Core Access and Mobility Management Function) entity or an SMF (Session Management Function) entity.
In some embodiments, the length of the analysis time interval for each analysis task is configured or adjusted by the NWDAF entity or the core network element within a time range provided by the network entity subscribing to the analysis task.
For example, the network entity subscribing to the analysis task provides a time range of (60ms, 150ms), and the length of the analysis interval of the analysis task is configured to be 80 ms.
In some embodiments, the length of the analysis time interval of each analysis task is configured or adjusted by the NWDAF entity or the core network element according to one or more of a collection time length of network data required for executing the analysis task, a size of a data volume, a transmission delay, and a processing delay for executing the analysis task.
For example: and calculating the average value of the historical acquisition time of the network data required by executing a certain analysis task, so that the length of the analysis time interval of the analysis task is greater than the average value or is a multiple of the average value.
For example: the length of an analysis time interval of a certain analysis task is estimated according to the size of the data volume of network data required for executing the analysis task, and the larger the data volume is, the larger the length of the analysis time interval is.
For example, the length of the analysis time interval of the analysis task is estimated based on the transmission route of the network data required for executing the analysis task, and the more network nodes the transmission route passes through, the greater the length of the analysis time interval.
For example, the length of the meta-analysis time interval or the length of the analysis time interval of the analysis task is estimated according to the processing resource occupation manner of the NWDAF entity. For example, the greater the length of the meta-analysis time interval and the length of the analysis time interval of the analysis task for an NWDAF entity sharing a processing resource relative to an NWDAF entity monopolizing a processing resource.
In addition to the above example, the length of the analysis time interval of the analysis task may be configured or adjusted according to multiple items of the acquisition time length of the network data required for executing the analysis task, the size of the data volume, the transmission delay, and the processing delay for executing the analysis task. For example, the length of the analysis interval of the analysis task is determined in consideration of the size of the data amount of the network data required to perform the analysis task, the transmission delay, and the processing delay in combination.
In some embodiments, the length of the analysis time interval of each analysis task is configured or adjusted by the NWDAF entity or the core network element to be less than or equal to a preset value or less than or equal to a preset reporting period according to the type of the analysis task.
For example, if the analysis task is a real-time analysis task, the length of the analysis time interval of the analysis task may be adjusted to be less than or equal to a preset value (e.g., millisecond order) to achieve the quasi-real-time analysis.
For example, if the analysis task is a periodic analysis task, the length of the analysis time interval of the analysis task may be adjusted to be less than or equal to a preset reporting period, for example, the preset reporting period is an integer multiple of the analysis time interval, and the analysis result is returned after the preset reporting period is reached.
Fig. 2 shows a flow diagram of a method of network data analysis according to further embodiments of the present disclosure. The Analysis task is, for example, user equipment communication Analysis (UE communication Analysis).
As shown in fig. 2, the method of this embodiment includes:
in step 210, the Network Function (NF) entity sends an analysis task Request (set to NWDAF-AnalysisInfo-Request) or an analysis task subscription Request (set to NWDAF-AnalysisInfo-Subscribe) for the user equipment communication to the NWDAF entity to Request the NWDAF entity to analyze the user equipment communication data.
In step 212, after receiving the request sent by the NF entity, the NWDAF entity configures an analysis time interval (e.g. T1 ═ 2 × T0 ═ 20 seconds) for the ue communication analysis task based on the meta-analysis time interval (e.g. T0 ═ 10 seconds), and starts a timer.
Then, the NWDAF entity collects the ue communication data to the network entities related to the analysis task, such as an Application Function (Application Function) entity, an SMF entity, an AMF entity, and the like, which may be specifically referred to in steps 220a to 220 f.
At step 220a, the NWDAF entity sends an event exposure subscription request (set to Naf-EventExposure-Subscribe) to the AF entity.
In step 220b, after the AF entity has the ue communication data, it returns the data to the NWDAF entity through an event exposure notification message (set as Naf-EventExposure-Notify).
At step 220c, the NWDAF entity sends an event exposure subscription request (set to Nsmf-EventExposure-Subscribe) to the SMF entity.
In step 220d, after the SMF entity has the ue communication data, an event exposure notification message (Nsmf-EventExposure-Notify) is returned to the NWDAF entity.
At step 220e, the NWDAF entity sends an event exposure subscription request (set to Namf-EventExposure-Subscribe) to the AMF entity.
In step 220f, after the AMF entity has the ue communication data, it returns to the NWDAF entity through an event exposure notification message (set as Namf-EventExposure-Notify).
In step 230, the NWDAF entity analyzes the collected user equipment communication data.
In step 234, if there is an analysis result available for output, the NWDAF entity determines whether the timer reaches the analysis time interval of the ue communication analysis task (e.g. T1 ═ 2 × T0 ═ 20 seconds), and if so, step 240 may be executed, otherwise, it needs to wait and step 240 cannot be executed. And, if the NWDAF entity determines that the timer has reached the time-sharing interval of the ue communication analysis task (e.g. T1-2 xT 0-20 seconds), but there is no analysis result available for output, the NWDAF resets the timer and restarts counting, and continues to perform step 230, i.e. continues to perform analysis in the next analysis interval.
In step 240, the NWDAF entity returns the analysis result to the NF entity through an analysis task Response message (set to NWDAF-AnalysisInfo-Response) or an analysis task notification message (NWDAF-AnalysisInfo-Notify).
In step 245, the NWDAF entity starts the timer again after returning the analysis result.
In step 250b, assuming that the AF entity has new ue communication data, it returns to the NWDAF entity again through an event exposure notification message (set as Naf-eventeexposure-Notify).
In step 250d, assuming that the SMF entity has new ue communication data, it returns to the NWDAF entity again through an event exposure notification message (set to Nsmf-EventExposure-Notify).
Furthermore, if the AF entity and the SMF entity generate new ue communication data before the timer reaches T1 time, the AF entity and the SMF entity immediately transmit the new ue communication data to the NWDAF entity, and the NWDAF entity performs analysis based on all ue communication data collected during the T1 time period and returns the analysis result once when the timer reaches T1.
In step 260, the NWDAF entity analyzes the collected user equipment communication data.
In step 267, if there is an analysis result available for output, the NWDAF entity determines whether the timer reaches the analysis time interval of the ue communication analysis task (e.g. T1 ═ 2 × T0 ═ 20 seconds), and if so, step 270 may be executed, otherwise, it needs to wait and step 270 cannot be executed. And, if the NWDAF entity determines that the timer has reached the time-sharing interval of the ue communication analysis task (e.g. T1-2 xT 0-20 seconds), but there is no analysis result available for output, the NWDAF resets the timer and restarts timing, and continues to perform step 260, i.e. continues to perform analysis in the next analysis interval.
In step 270, the NWDAF entity returns the analysis result to the NF entity through an analysis task Response message (set to NWDAF-AnalysisInfo-Response) or an analysis task notification message (NWDAF-AnalysisInfo-Notify).
Therefore, the analysis cycle problem occurring in the communication data analysis of the user equipment is solved, the running stability of the system is improved, the NWDAF entity obtains an analysis result based on a relatively stable system state, and the analysis effectiveness is improved.
Fig. 3 is a schematic diagram of an NWDAF entity of some embodiments of the present disclosure.
As shown in fig. 3, the NWDAF entity 300 of this embodiment includes: a memory 310 and a processor 320 coupled to the memory 310, the processor 320 configured to perform the method of network data analysis in any of the foregoing embodiments based on instructions stored in the memory 310.
As previously described, the processor 320 is configured to analyze the collected network data for each analysis task based on the analysis time interval for which the analysis task is configured; in a case where an interval between the current time and the time of sending out the analysis result of the analysis task last time is equal to or greater than an analysis time interval at which the analysis task is configured, for example, in a case where an interval between the current time and the time of sending out the analysis result of the analysis task last time is an integral multiple of the analysis time interval, sending the analysis result of this time to a network entity subscribing to the analysis task.
Wherein the analysis time interval of each analysis task is configured as one or more meta-analysis time intervals. The length of the analysis time interval of all analysis tasks is configured or adjusted by configuring or adjusting the length of the meta-analysis time interval. And configuring or adjusting the length of the analysis time interval of the analysis task by configuring or adjusting the number of the meta-analysis time intervals corresponding to each analysis task. The number of meta-analysis time intervals for different analysis tasks is the same or different.
In some embodiments, the length of the analysis time interval or the length of the meta-analysis time interval of each analysis task is configured or adjusted by the NWDAF entity or the core network element, for example, within a time range provided by the network entity subscribing to the analysis task, and the specific method for configuring or adjusting is referred to the foregoing, and will not be described herein again.
Fig. 4 is a schematic diagram of a network data analysis system according to some embodiments of the present disclosure.
As shown in fig. 4, the network data analysis system 400 of this embodiment includes: an NWDAF entity 300; and a network entity 410 subscribing to the analysis task, configured to send a subscription request of the analysis task to the NWDAF entity, and receive an analysis result returned by the NWDAF entity.
As previously described, the NWDAF entity 300 is configured to analyze the collected network data for each analysis task based on the analysis time interval for which the analysis task is configured; in a case where an interval between the current time and the time of sending out the analysis result of the analysis task last time is equal to or greater than an analysis time interval at which the analysis task is configured, for example, in a case where an interval between the current time and the time of sending out the analysis result of the analysis task last time is an integral multiple of the analysis time interval, sending the analysis result of this time to a network entity subscribing to the analysis task.
Wherein the analysis time interval of each analysis task is configured as one or more meta-analysis time intervals. The length of the analysis time interval of all analysis tasks is configured or adjusted by configuring or adjusting the length of the meta-analysis time interval. And configuring or adjusting the length of the analysis time interval of the analysis task by configuring or adjusting the number of the meta-analysis time intervals corresponding to each analysis task. The number of meta-analysis time intervals corresponding to different analysis tasks is the same or different.
In some embodiments, the length of the analysis time interval or the length of the meta-analysis time interval of each analysis task is configured or adjusted by the NWDAF entity or the core network element, for example, the length of the analysis time interval or the length of the meta-analysis time interval is configured or adjusted within a time range provided by the network entity subscribing to the analysis task, and reference is made to the foregoing description for specific methods for configuring or adjusting, which is not repeated herein.
In some embodiments, if the NWDAF entity 300 is not configured to configure or adjust the length of the analysis time interval or the length of the meta-analysis time interval for each analysis task, the network data analysis system 400 further comprises: the core network element 420, such as the AMF entity or the SMF entity, is configured to configure or adjust the length of the analysis time interval or the length of the meta-analysis time interval of each analysis task, and the specific method of configuration or adjustment is referred to the foregoing, and is not described herein again.
Some embodiments of the present disclosure propose a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method of network data analysis of any of the embodiments.
As will be appreciated by one skilled in the art, embodiments of the present disclosure may be provided as a method, system, or computer program product. Accordingly, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more non-transitory computer-readable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer program code embodied therein.
The present disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the disclosure. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only exemplary of the present disclosure and is not intended to limit the present disclosure, so that any modification, equivalent replacement, or improvement made within the spirit and principle of the present disclosure should be included in the scope of the present disclosure.
Claims (14)
1. A method of network data analysis, comprising:
the network data analysis function NWDAF entity analyzes the collected network data for each analysis task based on the configured analysis time interval of the analysis task;
and the NWDAF entity sends the analysis result of the time to a network entity subscribing the analysis task under the condition that the interval between the current time and the time of sending the analysis result of the analysis task last time is equal to or more than the configured analysis time interval of the analysis task.
2. The method of claim 1,
and the NWDAF entity sends the analysis result of the time to a network entity subscribing the analysis task under the condition that the interval between the current time and the time for sending the analysis result of the analysis task last time is integral multiple of the analysis time interval.
3. The method of claim 1, wherein the analysis time interval for each analysis task is configured as one or more meta-analysis time intervals.
4. The method of claim 3, further comprising:
the length of the analysis time interval of all analysis tasks is configured or adjusted by configuring or adjusting the length of the meta-analysis time interval.
5. The method of claim 3, further comprising:
and configuring or adjusting the length of the analysis time interval of each analysis task by configuring or adjusting the number of the meta-analysis time intervals corresponding to each analysis task.
6. The method of claim 3, wherein the number of meta-analysis time intervals corresponding to different analysis tasks is the same or different.
7. The method according to any one of claims 1 to 6,
the length of the analysis time interval or the length of the meta-analysis time interval of each analysis task is configured or adjusted by the NWDAF entity or the core network element.
8. The method of claim 7,
the length of the analysis time interval of each analysis task is configured or adjusted by the NWDAF entity or a core network element within a time range provided by a network entity subscribing to the analysis task.
9. The method of claim 7,
the length of the analysis time interval of each analysis task is configured or adjusted by the NWDAF entity or the core network element according to one or more of the acquisition time length of network data required for executing the analysis task, the size of data volume, transmission delay, and processing delay for executing the analysis task.
10. The method of claim 7,
the length of the analysis time interval of each analysis task is configured or adjusted to be less than or equal to a preset value or less than or equal to a preset reporting period by the NWDAF entity or the core network element according to the type of the analysis task.
11. A network data analysis function, NWDAF, entity, comprising:
a memory; and
a processor coupled to the memory, the processor configured to perform the method of network data analysis of any of claims 1-10 based on instructions stored in the memory.
12. A network data analysis system, comprising:
the network data analysis function, NWDAF, entity of claim 11; and
and the network entity subscribing the analysis task is configured to send a subscription request of the analysis task to the NWDAF entity and receive an analysis result returned by the NWDAF entity.
13. The system of claim 12, further comprising:
a core network element configured to configure or adjust a length of an analysis time interval or a length of a meta-analysis time interval of each analysis task.
14. A non-transitory computer-readable storage medium, having stored thereon a computer program which, when executed by a processor, carries out the steps of the method of network data analysis of any of claims 1-10.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2019192366A1 (en) * | 2018-04-04 | 2019-10-10 | 电信科学技术研究院有限公司 | Method and device for managing and controlling terminal ue |
| CN110383877A (en) * | 2017-03-10 | 2019-10-25 | 华为技术有限公司 | The system and method for network strategy optimization |
| CN110798360A (en) * | 2019-11-06 | 2020-02-14 | 腾讯科技（深圳）有限公司 | NWDAF network element selection method and device, electronic equipment and readable storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110383877A (en) * | 2017-03-10 | 2019-10-25 | 华为技术有限公司 | The system and method for network strategy optimization |
| WO2019192366A1 (en) * | 2018-04-04 | 2019-10-10 | 电信科学技术研究院有限公司 | Method and device for managing and controlling terminal ue |
| CN110798360A (en) * | 2019-11-06 | 2020-02-14 | 腾讯科技（深圳）有限公司 | NWDAF network element selection method and device, electronic equipment and readable storage medium |
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