Method and apparatus for data analytics in telecommunication network

Abstract

The present disclosure relates to a communication method and system for converging a 5th-Generation (5G) communication system for supporting higher data rates beyond a 4th-Generation (4G) system with a technology for Internet of Things (IoT). The present disclosure may be applied to intelligent services based on the 5G communication technology and the IoT-related technology, such as smart home, smart building, smart city, smart car, connected car, health care, digital education, smart retail, security and safety services. A method of managing analytics data in a telecommunication network is provided. The method includes a consumer Network Function, (NF), determines how analytics data from a plurality of individual sources is collected and analyzed in one of a) a distributed manner from a plurality of Network Data Analytics Functions (NWDAF), b) a centralized manner by aggregating analytics data from the plurality of NWDAFs, before analyzing it at an Aggregator NWDAF, or c) a mixture of a) and b) above.

Claims

1. A method performed by a consumer network function (NF) entity in a telecommunication network, the method comprising: transmitting, to a network repository function (NRF) entity, a discovery request; receiving, from the NRF entity, a discovery response comprising information for at least one network data analytics function (NWDAF) entity based on the discovery request; selecting an aggregator NWDAF entity from the at least one NWDAF entity, based on analytics aggregation capability information of the at least one NWDAF entity; transmitting, to the selected aggregator NWDAF entity, a subscription request comprising an analytics identifier (ID) and information for an area of interest; and receiving, from the selected aggregator NWDAF entity, a notification comprising aggregated analytics for the analytics ID.

2. The method of claim 1, wherein the aggregator NWDAF entity is configured to aggregate analytics for the analytics ID, received from other NWDAF entities associated with the area of interest.

3. The method of claim 1, wherein the analytics aggregation capability information of the at least one NWDAF entity is stored in the NRF entity.

4. The method of claim 2, wherein the aggregator NWDAF entity is configured to: determine the other NWDAF entities to aggregate analytics, based on configuration or queries to the NRF entity; transmit a subscription request to the determined other NWDAF entities; and receive a notification comprising the analytics for the analytics ID from the other NWDAF entities.

5. A consumer network function (NF) entity, the consumer NF entity comprising: a transceiver; and a controller configured to: transmit, to a network repository function (NRF) entity, a discovery request, receive, from the NRF entity, a discovery response comprising information for at least one network data analytics function (NWDAF) entity based on the discovery request, select an aggregator NWDAF entity from the at least one NWDAF entity, based on analytics aggregation capability information of the at least one NWDAF entity, transmit, to the selected aggregator NWDAF entity, a subscription request comprising an analytics identifier (ID) and information for an area of interest, and receive, from the selected aggregator NWDAF entity, a notification comprising aggregated analytics for the analytics ID.

6. The consumer NF entity of claim 5, wherein the controller is further configured to aggregate analytics from other NWDAF entities for the requested analytics ID for the area of interest.

7. The consumer NF entity of claim 5, wherein the analytics aggregation capability information of the at least one NWDAF entity is stored in the NRF entity.

8. A method performed by an aggregator network data analytics function (NWDAF) entity in a telecommunication network, the method comprising: receiving, from a consumer network function (NF) entity, a first subscription request comprising an analytics identifier (ID) and information for an area of interest; determining one or more other NWDAF entities to aggregate analytics, based on configuration or queries to a network repository function (NRF) entity; transmitting, to the determined one or more other NWDAF entities, a second subscription request for the analytics ID; receiving, from the determined one or more other NWDAF entities, a second notification comprising an analytics for the analytics ID; aggregating the analytics for the analytics ID; and transmitting, to the consumer NF entity, a first notification comprising the aggregated analytics for the analytics ID.

9. An aggregator network data analytics function (NWDAF) entity managing analytics data in a telecommunication network, the aggregator NWDAF entity comprising: a transceiver; and a controller configured to: receive, from a consumer network function (NF) entity, a first subscription request comprising an analytics identifier (ID) and information for an area of interest, determine one or more other NWDAF entities to aggregate analytics, based on configuration or queries to a network repository function (NRF) entity, transmit, to the determined one or more other NWDAF entities, a second subscription request for the analytics ID, receive, from the determined one or more other NWDAF entities, a second notification comprising an analytics for the analytics ID, aggregate the analytics for the analytics ID, and transmit, to the consumer NF entity, a first notification comprising the aggregated analytics for the analytics ID.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

(1) The above and other aspects, features, and advantages of certain embodiments of the disclosure will be more apparent from the following description taken in conjunction with the accompanying drawings, in which:

(2) FIG. 1 illustrates a general representation of a 5G network automation framework according to the related art;

(3) FIG. 2 illustrates a message exchange and method according to an embodiment of the disclosure;

(4) FIG. 3 illustrates a message exchange and method according to an embodiment of the disclosure;

(5) FIG. 4 illustrates a message exchange and method according to an embodiment of the disclosure; and

(6) FIG. 5 is a block diagram of a network entity according to an embodiment of the disclosure.

(7) Throughout the drawings, like reference numerals will be understood to refer to like parts, components, and structures.

DETAILED DESCRIPTION

(8) The following description with reference to the accompanying drawings is provided to assist in a comprehensive understanding of various embodiments of the disclosure as defined by the claims and their equivalents. It includes various specific details to assist in that understanding but these are to be regarded as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the various embodiments described herein can be made without departing from the scope and spirit of the disclosure. In addition, descriptions of well-known functions and constructions may be omitted for clarity and conciseness.

(9) The terms and words used in the following description and claims are not limited to the bibliographical meanings, but, are merely used by the inventor to enable a clear and consistent understanding of the disclosure. Accordingly, it should be apparent to those skilled in the art that the following description of various embodiments of the disclosure is provided for illustration purpose only and not for the purpose of limiting the disclosure as defined by the appended claims and their equivalents.

(10) It is to be understood that the singular forms “a,” “an,” and “the” include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to “a component surface” includes reference to one or more of such surfaces.

(11) FIG. 2 illustrates a scenario where there is a consumer NF, NRF, NWDAF(k) forming at least part of a system according to an embodiment of the disclosure. This also shows the various processes and messaging between respective elements.

(12) Referring to FIG. 2, it is assumed that index (k) shows the NWDAF instance ID in a multi-instance deployment. Each instance NWDAF(k) 120 is specialized in a set of data analytics types, identified by AnalyticsIDs(k); some overlapping across different instances and some are mutually exclusive. Instances with overlapping analytic IDs may help each other e.g. to cover different sets of UEs as the target of analytics reporting or to cover different set of Tracking Areas within the area of interest. Tracking Area Indicators—TAI(k) refers to such areas of interest that could be covered by NWDAF(k).

(13) Case A: Distributed Data Collection Model

(14) In a first embodiment of the disclosure, the Consumer NF 100, based on its implemented selection criteria, e.g. network configuration or pre-configured network operator's preference, may decide to consume different NWDAFs' services in a distributed manner.

(15) The details of each operation shown in FIG. 2 are as follows:

(16) 1. NWDAF service consumer 100 sends NF discovery request (1a) to NRF 110 including all required Analytics ID(s) and the area of interest (e.g. in form of TAIs). The request may also include extra information, e.g. Network Slice Selection Assistance Information (i.e. Single-NSSAI or S-NSSAI). The NRF 110 response (1b) may include multiple NWDAF instance IDs, NWDAF(k), each covering a set of Analytics ID(s), AnalyticsIDs(k), and (part of) the area of interest supported by instance (k), identified as TAI(k).

(17) 2. NWDAF service consumer 100 sends a subscription request (2a) to each NWDAF(k) 120 including AnalyticsIDs(k) and TAI(k) (e.g. as Analytics Filter). The request can be as the set of tuple of (AnalyticsIDs(k), Analytics Filter=TAI(k)) as shown in operation 2a to differentiate the area of interest per analytics ID. NWDAF(k) 120 notifies with analytics specific parameters per analytics ID as shown in operation 2b.

(18) 3. The service consumer NF 100 may aggregate the target of analytics reporting across NWDAF(k)s for AnalyticsIDs(k) for corresponding areas of interest TAI(k).

(19) Case B: (Semi-) Centralized Data Collection Model with AP ID

(20) FIG. 3 illustrates a scenario where there is a consumer NF, NRF, NWDAF(j) and NWDAF(i) forming at least part of a system according to an embodiment of the disclosure.

(21) Referring to FIG. 3, the Consumer NF 200 based on AP ID as assistance information in addition to its implemented selection criteria decides to consume different NWDAFs' services in a (semi-)centralized manner, designating one (set of) NWDAF(s) as aggregation point(s).

(22) In this case, when registering an aggregation point like NWDAF (j) 220 into NRF 210 in addition to the set of analytics IDs to be supported by NWDAF (j) 220 and area of interest to be covered by NWDAF (j) 220, the AP ID is also configured equivalent to NWDAF(j) 220 ID. This also identifies NWDAF(j) 220 as an aggregation point.

(23) When registering a distributed NWDAF like NWDAF(i) 230 within NRF 210, in addition to the set of analytics IDs to be supported by NWDAF(i) 230 and the area of interest to covered by NWDAF(i) 230, the AP ID is also configured equivalent to one of NWDAF(j)s 220 already registered as aggregation points.

(24) The mapping between NWDAF(j)s 220 and NWDAF(i)s 230 in AP IDs can take into account multiple factors including the level of load per NWDAF, analytics IDs supported per NWDAF, area of interest supported per NWDAF, any predefined hierarchy for mapping or other KPIs set by the network operator. NWDAF information maintained in NRF 210 or any other designated Data Repository structures may hold this mapping between NWDAFs based on AP IDs. In case B, both NRF 210 and NWDAF service consumer 200 become aware of the mapping between central and distributed NWDAFs based on AP IDs.

(25) FIG. 3 illustrates a scenario where there is a consumer NF, NRF, NWDAF(j) and NWDAF(i) forming at least part of a system according to an embodiment of the disclosure. The details of each operation shown in FIG. 3 are as follows:

(26) 1. Similar to operation 1 of case A shown in FIG. 2 (distributed deployment), except the NRF 210 response may include both distributed NWDAF(i)s and central NWDAF(j)s. The NRF 210 response also includes the AP ID per NWDAF(i) 230 instance indicating possible aggregation point(s) NWDAF(j) 220 for different values of (j) i.e. the mapping between central and distributed NWDAFs. NWDAF service consumer 200 determines central aggregation points based on the mapping received from NRF 210 as AP IDs.

(27) 2. NWDAF service consumer 200 sends a subscription request to NWDAF(j) 220 (to designate it as an aggregation point) including AnalyticsIDs(i), TAI(i) (as analytics filter) for NWDAF(i) 230. NWDAF(j) 220 identifies its designation as aggregation point being the addressee of service consumer request. Alternatively, another explicit flag or parameter can be set as an input parameter by NWDAF service consumer 200 to explicitly designate an aggregation point, NWDAF(j) 220.

(28) 3. NWDAF(j) 220 subscribes to all NWDAF(i)s 230 in a similar procedure as case A (single instance subscription procedure). All NWDAF(i)s notify with analytics specific parameters per analytics ID in the set of AnalyticsIDs(i).

(29) 4. NWDAF(j) 220 may aggregate the target of analytics reporting across different NWDAF(i)s 230 for AnalyticsIDs(i) for corresponding area of interest, TAI(i).

(30) 5. NWDAF(j) 220 notifies with analytics specific parameters per analytics ID for all aggregated analytics IDs per NWDAF(i) 230.

(31) Case C: (Semi-) Centralized Data Collection Model without AP ID

(32) In an alternative embodiment of the disclosure, similar to case B, operation 1 is exactly similar to case A (distributed deployment) where the data kept in NRF 210 or any other data repository structure stays agnostic to deployment information (i.e. aggregation point identifiers). As a result, the NWDAF service consumer 200 decides on aggregation point(s) without any other assistance information.

(33) In another case of centralized aggregation (termed here as case C), no mapping is indicated between central and distributed NWDAFs at NRF 210. In this case, no AP ID is configured for NWDAFs and only aggregation points are differentiated when registering in NRF 210 either implicitly (refer to case D, which follows) or explicitly e.g. by configuring an identifier. In case C, NRF 210 becomes agnostic to the mapping between central and distributed NWDAFs.

(34) The details of each operation are as follows:

(35) 1. Similar to operation 1 of case A shown in FIG. 2, except NRF 210 response may include both distributed NWDAF (i)s 230 and NWDAF (j)s 220 identified as aggregation points. NWDAF service consumer 200 determines central aggregation point(s) based on its configuration or implemented selection criteria.

(36) 2-5. are as above described for case B.

(37) Case D: (Semi-) Centralized Data Collection Model, Pre-Negotiated

(38) In an alternative embodiment of the disclosure similar to case B, operation 1 is similar to case A (distributed deployment) except in respect of the data kept within NRF 210 or any other data repository structure, the AnalyticsIDs(j) advertised by NWDAF(j) 220 is an extended set of analytics IDs from different NWDAF(i)s 230 that can be pre-negotiated for instance j, e.g. based on some configurations or a pre-defined hierarchy when each NWDAF registers within NRF 210. As a result, no explicit identifier is defined per NWDAF within NRF 210, unlike case B and no mapping is indicated between central and distributed NWDAFs at NRF 210.

(39) The extended set of analytics IDs supported can be differentiated from analytics IDs directly supported per NWDAF. Some central NWDAFs may only aggregate analytics so the extended list may not have directly supported analytics in such a situation. Consequently, the NWDAF service consumer 200 may utilize this information in addition to its implemented selection criteria to decide on how multiple NWDAFs collaborate (e.g. the NWDAF(s) supporting more analytics IDs directly can be preferred to extend their list to avoid extra signaling overhead or network latency).

(40) The details of each operation are as follows:

(41) 1. Similar to operation 1 of case A shown in FIG. 2, except NRF 210 response may include both distributed NWDAF (i)s 230 and NWDAF (j)s 220 identified as aggregation points. NWDAF service consumer 200 determines central aggregation point based on its implemented selection criteria.

(42) 2. NWDAF service consumer sends subscription request to NWDAF(j) 220 (to designate as aggregation point) including all Analytics IDs, TAIs needed without indicating any mapping per NWDAF (i)s 230.

(43) 3. NWDAF (j) 220 based on extended set of supporting analytics IDs and also configuration, implementation or queries to NRF 210, decides on mapping to specific distributed NWDAFs to aggregate analytics from and subscribes to them.

(44) 4. NWDAF(j) 220 may aggregate the target of analytics reporting across different NWDAF(i)s 230 for Analytics IDs(i) for corresponding area of interest.

(45) 5. NWDAF (j) 220 notifies with analytics specific parameters per analytics ID for all aggregated analytics IDs without indicating any mapping per NWDAF(i)s 230.

(46) Case D1: (Semi-) Centralized Data Collection Model, Mapping at Central NWDAFs

(47) In another case of centralized aggregation (referred to here as case D1, as a sub-case of Case D), no mapping is indicated between central and distributed NWDAFs at NRF 210 similar to case D. In this option also, no AP ID configured and only aggregation points are differentiated when registering in NRF 210 either implicitly (again similar to case D) or explicitly e.g. by configuring an identifier. Furthermore, in addition to NRF 210, NWDAF service consumer 200 also becomes agnostic to the mapping between central and distributed NWDAFs. Instead, each central NWDAF 220 based on configuration, implementation or queries to NRF 210 or a pre-defined hierarchy (when registers to NRF) decides on mapping to specific distributed NWDAFs.

(48) The details of each operation are as follows:

(49) 1. Similar to operation 1 of case A shown in FIG. 2, except NRF 210 response may include both distributed NWDAF (i)s 230 and NWDAF (j)s 220 identified as aggregation points. NWDAF service consumer 200 chooses central aggregation points.

(50) 2. NWDAF service consumer sends subscription request to NWDAF(j) 220 (to designate as aggregation point) including all Analytics IDs, TAIs needed without indicating any mapping of analytics IDs or TAIs per NWDAF (i) 230.

(51) 3. NWDAF (j) 220 based on configuration, implementation or queries to NRF 210 decides on mapping to specific distributed NWDAFs 230 to aggregate analytics from and accordingly subscribes to them.

(52) 4. NWDAF(j) 220 may aggregate the target of analytics reporting across different NWDAF(i)s 230 for Analytics IDs(i) for corresponding areas of interest.

(53) 5. NWDAF (j) 220 notifies with analytics specific parameters per analytics ID for all aggregated analytics IDs without indicating any mapping of analytics IDs or TAIs per NWDAF (i) 230.

(54) Case E: Mixed Mode Data Collection Model

(55) In third embodiment of the disclosure, a mixture of distributed and (semi-) centralized modes of deployment can be used.

(56) FIG. 4 illustrates a scenario where there is a consumer NF, NRF, NWDAF(k), NWDAF(j) and NWDAF(i) forming at least part of a system according to an embodiment of the disclosure.

(57) Referring to FIG. 4, the details of each operation are as follows:

(58) 1. NWDAF service consumer 300 sends NF discovery request (1a) to NRF 310 including all required Analytics ID(s) and the area of interest (e.g. in form of TAIs). The request may also include extra information, e.g. Network Slice Selection Assistance Information (i.e. Single-NSSAI or S-NSSAI). NRF response may include (1b) a (set of) NWDAF instance ID(s), i.e. NWDAF(k) 320, deployed in distributed manner. NRF 310 response may also include (1c) a (set of) NWDAF instance ID(s) (i.e. NWDAF(i) 340) to be aggregated in a (set of) NWDAF instance IDs (i.e. NWDAF(j) 330).

(59) 2. NWDAF service consumer 300 subscribes to all NWDAF(k)s 320 similar to the distributed deployment procedure in case A and receives individual notifications.

(60) 3. NWDAF service consumer 300 also subscribes to NWDAF(j) 330. NWDAF(j) 330 subscribes to all relevant NWDAF(i)s 340 to be aggregated similar to the (semi-)centralized deployment procedure in cases B or C or D or D1 and provides aggregate notification to the NWDAF service consumer 300.

(61) 4. The NWDAF service consumer 300 aggregates analytics data from both distributed and (semi-)centralized NWDAF instances.

(62) FIG. 5 is a block diagram of a network entity according to an embodiment of the disclosure. The network entity may correspond to each of the network entities shown in FIGS. 1-4. For example, the network entity may refer to each of the network functions (e.g. NRF, NWDAF) shown in FIG. 1-4.

(63) Referring to FIG. 5, the network entity may include a transceiver 510, a controller 520, and storage 530. In the present disclosure, the controller 520 may include a circuit, an ASIC, or at least one processor.

(64) The transceiver 510 may transmit and receive signals to and from a terminal or another network entity.

(65) The controller 520 may control the overall operation of the network entity according to an embodiment. For example, the controller 520 may control the signal flow to perform the operations in FIGS. 1-4 described above. For example, the control unit 520 may determining how analytics data from a plurality of individual sources is collected and analyzed.

(66) The storage 530 may store at least one of information exchanged through the transceiver 510 and information generated by the controller 530.

(67) At least some of the example embodiments described herein may be constructed, partially or wholly, using dedicated special-purpose hardware. Terms such as ‘component’, ‘module’ or ‘unit’ used herein may include, but are not limited to, a hardware device, such as circuitry in the form of discrete or integrated components, a Field Programmable Gate Array (FPGA) or Application Specific Integrated Circuit (ASIC), which performs certain tasks or provides the associated functionality. In some embodiments, the described elements may be configured to reside on a tangible, persistent, addressable storage medium and may be configured to execute on one or more processors. These functional elements may in some embodiments include, by way of example, components, such as software components, object-oriented software components, class components and task components, processes, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays, and variables. Although the example embodiments have been described with reference to the components, modules and units discussed herein, such functional elements may be combined into fewer elements or separated into additional elements. Various combinations of optional features have been described herein, and it will be appreciated that described features may be combined in any suitable combination. In particular, the features of any one example embodiment may be combined with features of any other embodiment, as appropriate, except where such combinations are mutually exclusive. Throughout this specification, the term “comprising” or “comprises” means including the component(s) specified but not to the exclusion of the presence of others.

(68) Attention is directed to all papers and documents which are filed concurrently with or previous to this specification in connection with this application and which are open to public inspection with this specification, and the contents of all such papers and documents are incorporated herein by reference.

(69) All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and/or all of the operations of any method or process so disclosed, may be combined in any combination, except combinations where at least some of such features and/or operations are mutually exclusive.

(70) Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise. Thus, unless expressly stated otherwise, each feature disclosed is one example only of a generic series of equivalent or similar features.

(71) While the disclosure has been shown and described with reference to various embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the disclosure as defined by the appended claims and their equivalents.