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20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 7.5 A-DCCF ID | The A-DCCF ID uniquely identifies the application data collection and coordination function. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 7.6 Data Producer ID | The Data Producer ID uniquely identifies the data producer / source which is used as input for application data analytics enablement services. Data Producer based on the analytics event, can be either a network function or a management domain function/service or an application server or client or an edge / cloud service. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 7.7 ADAE service area | The ADAE service area is the area where the Application Data Analytics Enablement server owner provides its analytics services. It is equal to the coverage area for which analytics apply.
The ADAE service area can be expressed as a Topological Service Area (e.g. a list of TA), a Geographical Service Area (e.g. geographical coordinates) or both. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 7.8 Analytics ID | The analytics ID (or analytics event ID) identifies the application layer analytics event which corresponds to the specified ADAE analytics services. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8 Procedures and information flows | |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.1 General | This clause describes the procedures and the information flows related to the ADAE capabilities, as introduced in clause 6. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.2 Procedure on support for application performance analytics | |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.2.1 General | In this functionality, two procedures are described in more detail in clause 8.2.2 and 8.2.3 accordingly:
- one procedure for VAL server related analytics where an example in provided for VAL server performance,
- one procedure for VAL session/UE related analytics. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.2.2 Procedure on VAL server performance analytics | Figure 8.2.2-1 illustrates the procedure where the VAL server performance analytics are performed based on data collected from the ongoing VAL sessions as well as data from the DN (VAL server, DN database or networking stack at the DN).
Pre-conditions:
1. ADAE Client (ADAEC) is connected to ADAES.
2. Data producers (e.g. A-ADRF, VAL Client) may be pre-configured with data producer profiles for the data they can provide. ADAES and ADAEC have discovered available data producers and their data producer profiles.
Figure 8.2.2-1: ADAES support for VAL server performance analytics
1. The consumer of the ADAES analytics service sends a VAL performance analytics subscription request to ADAES and provides the analytics event ID e.g. "VAL server performance analytics".
2. The ADAES sends a subscription response as a positive or negative acknowledgement to the consumer of the analytics service.
3. The ADAES maps the analytics event ID to a list of data collection event identifiers, and a list of data producer IDs. Such mapping may be preconfigured by OAM or may be determined by ADAES based on the analytics event type / vertical type and/or data producer profile.
4. The ADAES sends a data collection subscription request to the Data Producers (at the DN side or UE side) with the respective Data Collection Event ID and the requirement for data collection. Such data producers include the A-ADRF, the A-DCCF, the VAL server, SEALDD server, or the VAL UEs.
5. The Data Producer(s) sends a subscription response as a positive or negative acknowledgement to the ADAES.
NOTE: The ADAES acting as AF may also subscribe to NEF/SMF/PCF/NWDAF to monitor network/UE situation or network data analytics required for the application data analytics event.
6. The ADAES based on subscription, may receive offline stats/data from A-ADRF on the VAL server performance based on the analytics/data collection event ID. Such offline data can be average/peak throughput, average/maximum e2e delay, jitter, average application layer PER, availability, VAL server load, number of failed transactions, and can be for a given area and time of the day (based on the time/area of the request).
A session starts between the VAL server #1 and a UE (this could happen for more than one UEs).
7. The Data Producer at DN side, starts collecting data from the data generating entities, e.g. real-time networking or application data (from networking start at DN or VAL server itself), such as RTT, application layer PER, throughput.
8a. The Data Producer sends the real-time data to the ADAES, where the data correspond to the data collection ID or the analytics event ID for which the ADAES subscribed.
8b. The ADAES may receive also data (periodically or if a threshold is reached based on configuration) from the application of the UE within the ongoing session (via ADAEC). Such data can be about the RTT, average/peak throughput, jitter, QoE measurements (MOS, stalling events, stalling ratios, etc), QoS profile load, VAL server load, etc.
9. When the VAL UE session with VAL server finishes, the ADAEC notifies the ADAES of the completion of the reporting.
10. The ADAES abstracts or correlates the data based on the analytics event and the data collection configuration. Such correlation can be filtering of data for the same metrics but with different granularities or be combining/aggregating the data of segments of the end-to-end path (end to end is between VAL client and server). The outcome is an abstracted/correlated/filtered set of data.
11. The ADAES derives application layer analytics on VAL server #1 performance, based on the analytics ID and type of request. Such analytics can be stats or prediction for a given area/time and based on the event type for a given network configuration.
12. The ADAES sends the analytics to the consumer, where these analytics include the VAL server #1 predicted or statistic performance for a given area and time horizon, including also the confidence level.
NOTE: If the Data Producer in steps 4-5 and 8a is SEALDD server, procedure in clause 9.7.2.1 of 3GPP TS 23.433 [13] is used for the collection of the E2E transmission quality measurement results to ADAES. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.2.3 Procedure on VAL session performance analytics | Figure 8.2.3-1 illustrates the procedure where the VAL session performance analytics are performed based on data collected from the ongoing VAL sessions.
Pre-conditions:
1. ADAEC is connected to ADAES.
2. Data producers (e.g. A-ADRF, VAL Client) may be pre-configured with data producer profiles for the data they can provide. ADAES and ADAEC have discovered available data producers and their data producer profiles.
Figure 8.2.3-1: ADAES support for VAL session performance analytics
1. The consumer of the ADAES analytics service sends a VAL performance analytics subscription request to ADAES and provides the analytics event ID e.g. "VAL session performance analytics", the target VAL UE ID, VAL server ID/VAL application ID, the time validity and area of the request, the required confidence level, exposure level for providing UE analytics. If the consumer is the VAL server, the VAL server can provide to ADAEC application data related to the UE expected route/trajectory and VAL application traffic schedule / expected session time.
2. The ADAES sends a subscription response as an ACK to the consumer.
3. The ADAES selects the corresponding ADAEC of the VAL UE for which the local analytics need to be performed.
4a. The ADAES sends a subscription request to the ADAEC with the analytics event ID and the configuration of the reporting required (e.g., periodic, based on event with threshold).
4b. The ADAEC sends a subscription response to ADAES.
5. The ADAEC maps the analytics event ID to a list of data collection event identifiers or data collected IDs at the VAL UE or other UEs within the service and in proximity (in group-based communications). The ADAEC also determines the data producers using the analytics event ID, target data producer profile and optional preconfigured policies.
6. The ADAEC subscribes to the VAL clients and/or requests UE local data based on the respective Data Collection Event ID (or the analytics event ID if they already know the mapping). This data may come from the PDU layer of the UE (via listening the traffic), or via VAL client of one or more UEs (if an application consists of a group of UEs).
A session starts between the VAL UE #1 and a VAL server.
7. The ADAEC (after being aware from the VAL client that the session started) sends a notification to ADAES that a session started, and it could be possible to provide real-time data analytics for VAL UE performance in the target area.
8. The ADAEC starts collecting data from the corresponding data producers based on subscription. Such data can be about the RTT, throughput, jitter, QoE measurements, QoS profile load, etc. It can be also possible that VAL client provides to ADAEC application data related to the UE expected route/trajectory and VAL application traffic schedule / expected session time.
9. The ADAEC filters or correlates the data based on the analytics event and the data collection configuration.
10. When the VAL UE session finishes, the ADAEC (optionally) derives VAL session analytics to ADAES on VAL UE #1 performance, based on the analytics ID and type of request. Such analytics (if performed at the ADAEC can be stats or predictions on the RTT or RTT deviation, average/peak throughput, jitter, QoE measurements (MOS, stalling events, buffer related events), QoS profile load, VAL application traffic load etc. In case of prediction, a confidence level shall be also present and a time horizon for the predicted parameters.
11. The ADAEC sends the data of step 9 or the analytics of step 10 (if ADAEC performs analytics) to the ADAES.
12. The ADAES derives application layer analytics on VAL session performance (based on the data or analytics received by the ADAEC), based on the analytics ID and type of request. Such analytics can be stats or prediction for a given area/time and based on the event type for a given network configuration. Such analytics (if no analytics is performed at ADAEC) at ADAES can be stats or predictions on the RTT or RTT deviation, average/peak throughput, jitter, QoE measurements, QoS profile load, VAL application traffic load etc. In case of prediction, a confidence level shall be also present and a time horizon for the predicted parameters.
13. The ADAES sends the analytics to the consumer, where these analytics include the VAL UE #1 session predicted or statistic performance for a given area and time horizon, including also the confidence level. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.2.4 Information flows | |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.2.4.1 General | The following information flows are specified for VAL performance analytics based on 8.2.2 and 8.2.3. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.2.4.2 VAL performance analytics subscription request | Table 8.2.4.2-1 describes information elements for the VAL performance analytics subscription request from the consumer (e.g. VAL server, NF, AF) to the ADAE server or from ADAE server to ADAE client.
Table 8.2.4.2-1: VAL performance analytics subscription request
Information element
Status
Description
Consumer ID
M
The identifier of the analytics consumer.
Analytics ID
M
The identifier of the analytics event. This ID can be for example “VAL server performance analytics” for procedure in 8.2.2, or “VAL session performance analytics” for procedure in 8.2.3.
Analytics type
M
The type of analytics for the event, e.g. statistics or predictions.
VAL service ID
M
The identifier of the VAL service for which analytics subscription applies.
Target VAL UE ID(s)
O
The VAL UE identifier(s) for which the analytics subscription applies.
Target VAL server ID
O
If consumer is different from the VAL server, this identifier shows the target VAL server for which the analytics subscription applies (for procedure in 8.2.2).
Target data producer profile criteria
O
Characteristics of the data producers to be used.
ADAE client application data
O
Represent ADAE client application data (e.g. related to the UE expected route/trajectory and VAL application traffic schedule/expected session time) that the consumer can provide, if the consumer is VAL server.
Preferred confidence level
O
The level of accuracy for the analytics service (in case of prediction).
Area of Interest
O
The geographical or service area for which the subscription request applies.
Time validity
O
The time validity of the subscription request.
Exposure level requirement
O
The level of exposure requirement (e.g. condition on providing UE analytics like threshold is reached) for the UE analytics to be exposed.
Reporting requirements
O
It describes the requirements for analytics reporting. This requirement may include e.g. the type and frequency of reporting (periodic or event triggered), the reporting periodicity in case of periodic, and reporting thresholds in case of event triggered. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.2.4.3 VAL performance analytics subscription response | Table 8.2.4.3-1 describes information elements for the VAL performance analytics subscription response from the ADAE server to the consumer (e.g. VAL server, NF, AF) or from ADAE client to ADAE server.
Table 8.2.4.3-1: VAL performance analytics subscription response
Information element
Status
Description
Result
M
The result of the analytics subscription request (positive or negative acknowledgement). |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.2.4.4 Data collection subscription request | Table 8.2.4.4-1 describes information elements for the Data collection subscription request from the ADAE server to the Data Producer (e.g., A-DCCF, A-ADRF, VAL server, SEALDD server, or VAL UE via ADAE client).
Table 8.2.4.4-1: Data collection subscription request
Information element
Status
Description
ADAE server ID
M
The identifier of the ADAE server.
Data Collection Event ID
M
The identifier of the data collection event.
Data Collection requirements
M
The requirements for data collection, including the format of data, frequency of reporting, level of abstraction of data, level of accuracy of data.
Analytics ID
O
The identifier of the analytics event, for which the data collection is needed.
List of Data Producer IDs
O
In case when this request is performed via A-DCCF, then the list of Data Producer IDs is needed.
Target VAL UE ID(s) and address(es)
O
The VAL UE identifier(s) and IP address(es) for which the data collection subscription applies.
Target VAL server ID
O
This identifier shows the target VAL server for which the data collection subscription applies.
Target data producer profile criteria
O
Characteristics of the data producers to be used.
Area of Interest
O
The geographical or service area for which the requirement request applies.
Interest time period
O
Interested time period for which the requirement request applies (e.g. time of the day).
Time validity
O
The time validity of the request |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.2.4.5 Data collection subscription response | Table 8.2.4.5-1 describes information elements for the Data collection subscription response from the Data Producer (e.g., A-DCCF, A-ADRF, VAL server, SEALDD server, or VAL UE via ADAE client) to the ADAE server.
Table 8.2.4.5-1: Data collection subscription response
Information element
Status
Description
Result
M
The result of the data collection subscription request (positive or negative acknowledgement). |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.2.4.6 Data Notification | Table 8.2.4.6-1 describes information elements for the Data Notification from the Data Producer to the ADAE server.
Table 8.2.4.6-1: Data notification
Information element
Status
Description
Data Collection Event ID
M
The identifier of the data collection event.
Target VAL UE ID and address(es)
M (NOTE)
The VAL UE identifier(s) and IP address(es) for which the data apply.
Target VAL server ID
M (NOTE)
This identifier of the target VAL server for which the data applies.
Analytics ID
O
The identifier of the analytics event. This ID can be for example “VAL server performance analytics” for procedure in 8.2.2, or “VAL session performance analytics” for procedure in 8.2.3.
Data Type
O
The type of reported data samples which can be UE data, network data, application data, edge data, or different granularities / abstraction of data (e.g. real time, non real time).
Data Output
M
The reported data, which can be inform of measurements or offline/historical data on the requested parameter based on subscription. For example:
• offline stats/data from A-ADRF on the VAL server performance based on the analytics/data collection event ID. Such offline data can be average/peak throughput, average/maximum e2e delay, jitter, average application layer PER, availability, VAL server load, number of failed transactions, and can be for a given area and time of the day (based on the time/area of the request).
• from the application of the UE within the ongoing session (via ADAEC). Such data can be about the RTT, average/peak throughput, jitter, QoE measurements (MOS, stalling events, stalling ratios, etc), QoS profile load, VAL server load, etc.
NOTE: One of these shall be present based on the data collection event |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.2.4.7 Analytics Notification | Table 8.2.4.7-1 describes information elements for the Analytics Notification from the ADAE server to the consumer (e.g. VAL server, NF, AF).
Table 8.2.4.7-1: Analytics notification
Information element
Status
Description
Analytics ID
M
The identifier of the analytics event. This ID can be for example “VAL server performance analytics” for procedure in 8.2.2, or “VAL session performance analytics” for procedure in 8.2.3.
Analytics Output
M
The analytics outputs, which can be predictive or statistical parameter.
> VAL server performance analytics output
O
(see NOTE)
Statistics or predictions of the VAL server performance, such as RTT, average/peak throughput, jitter, QoE measurements, QoS profile load, VAL server load, VAL server predicted or expected performance change for the requesting consumer.
> VAL session performance analytics output
O
(see NOTE)
Statistics or predictions of the VAL session performance, such as RTT, average/peak throughput, jitter, QoE measurements, QoS profile load, VAL application traffic load, VAL session predicted or expected performance change.
Applicable area
M
The service area or geographical area for which the analytics output applies to.
Confidence level
O
(see NOTE)
The achieved confidence level.
Time horizon
O
(see NOTE)
The time horizon for predictive analytics.
> Start time
O
The start time point of predictive validity. If omitted, the default value is the current time.
> End time
M
The end time point of predictive validity.
NOTE: One of the IEs shall be present based on the Analyitcs ID provided in the subscription request. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.2.4.8 Data producer profile | The data producer profile IE includes information about the data generation/production capability of the data producer to support data collection for data analytics service and the availability/accessibility of the generated/produced data, as defined in Table 8.2.4.8-1.
Table 8.2.4.8-1: Data producer profile
Information element
Status
Description
Data Producer ID
M
ID of the data producer.
Data producer type (NOTE)
M
Specifies the type of the data producer, e.g., ADAEC, A-DCCF, A-ADRF, VAL server, SEAL server, SEAL client, EES, EAS.
Data type (NOTE)
M
Type of information that can be provided by the data producer, e.g., performance indicators, reproducer usage data, server load data, application performance, edge load.
Data producer role (NOTE)
O
Role of the data producer, e.g., generating entity, original producer, repository.
Original producer ID (NOTE)
O
If the data producer role is not “original producer” or “generating entity”, specifies the Producer ID of the original data producer for the data provided by this data producer.
If the data producer type is A-DCCF, this is a list of Data Producer IDs.
Data freshness (NOTE)
O
If the data producer role is not “original producer” or “generating entity”, length of time elapsed after the data is generated until is available at the data producer. Alternatively, the data collection rate supported by the producer is provided.
Data producer capability (NOTE)
O
Indicates data producer capabilities for this data type, e.g. how long the data can be stored, support for anonymization, data generation rate and schedule.
NOTE: When the Data producer profile IE is used for Target data producer profile criteria (e.g. Table 8.2.4.4-1), this IE may be a list of values. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.3 Procedure on support for slice-specific application performance analytics | |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.3.1 General | This clause describes the procedure for supporting slice-specific application performance analytics. The ADAES service consumer can subscribe and receive notifications about slice specific application performance analytics events. In case that the ADAES consumer needs information about historical data, the procedure in 8.7.3 can be used for retrieving of slice-specific application performance metrics data about a specific area and time window in the past. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.3.2 Procedure | Figure 8.3.2-1 illustrates the procedure where the VAL server performance analytics are performed based on data collected from the ongoing VAL sessions as well as data from the DN (VAL server, DN database or networking stack at DN) for a specific slice.
Pre-conditions:
1. ADAEC is connected to ADAES.
Figure 8.3.2-1: ADAES support for slice-related performance analytics
1. The consumer of the ADAES analytics service sends a subscription request to ADAES and provides the analytics event ID e.g. "slice-specific application performance analytics ", the target S-NSSAI, DNN, NSI ID, the time validity of the request, the required confidence level, area and time horizon, etc.
2. The ADAES sends a subscription response as an ACK to the consumer.
3. The ADAES subscribes to the Data Sources with the respective Data Collection Event ID and the requirement for data collection related to the request slice(s). Such requests may be towards:
- OAM for providing PM data related to the requested slice / NSI. Alternatively, if the interaction to OAM happens via NSCE layer (see TS 23.435 [6]), such subscription can be performed to NSCE (where ADAES is acting as VAL server).
- NWDAF for providing slice related analytics for the given area and time horizon (indicated in step 1). Such analytics can be the slice load level related network data analytics, or the service experience related network data analytics for a given slice.
4. The ADAES based on subscription, receives PM data notification from OAM or from NSCE server (via OAM APIs or NSCE-S APIs)
5. The ADAES based on subscription, receives the requested NWDAF analytics outputs. Such analytics can be:
- network slice or NSI statistics or predictions (clause 6.3.3A of TS 23.288 [4])
- per slice instance service experience stats or predictions (clause 6.4.3 of TS 23.288 [4])
6. The ADAES can also provide analytics on the VAL session performance (based on the procedure of clause 8.2.2 step 11 or clause 8.2.3 step 12) and filters the analytics only for the sessions which are connected to that requested slice for the area of interest.
7. The ADAES abstracts or correlates the data/analytics from steps 4-6 and provides analytics on the slice or NSI performance for the target VAL application/server. For example, such analytics can be about the min/average/max predicted RTT / end to end latency for the VAL application/server if this server uses a given slice/NSI (or for a list of given slices) within an area of interest.
8. The ADAES sends the analytics to the consumer, as a slice-specific performance analytics notification message. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.3.3 Information flows | |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.3.3.1 General | The following information flows are specified for slice-specific application performance analytics based on 8.3.2. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.3.3.2 Slice-specific performance analytics subscription request | Table 8.3.3.2-1 describes information elements for the slice-specific performance analytics subscription request from the consumer (VAL server / NSCE server) to the ADAE server.
Table 8.3.3.2-1: Slice-specific performance analytics subscription request
Information element
Status
Description
Consumer ID
M
The identifier of the analytics consumer.
Analytics ID
O
The identifier of the analytics event. This ID can be for example “slice-specific application performance analytics”.
Analytics type
M
The type of analytics for the event, e.g. statistics or predictions.
Slice identifier(s)
M
The identifier(s) of the target slice(s) or slice instance(s), i.e. S-NSSAI, NSI ID or ENSI.
DNN
O
The target DNN for which the request applies.
Target VAL UE ID(s)
O
The VAL UE(s) for which the analytics subscription applies.
Target VAL server ID
O
If consumer is different from the VAL server, this identifier shows the target VAL server for which the analytics subscription applies (for procedure in clause 8.3.2).
Target VAL service ID
O
The identifier of the VAL service for which the analytics applies.
Preferred confidence level
O
The required level of accuracy for the analytics service (in case of prediction).
Area of Interest
O
The geographical or service area for which the subscription request applies.
Time validity
O
The time validity of the subscription request.
Time horizon
O
The required time horizon for predictive analytics.
> Start time
O
The start time point of predictive validity. If omitted, the default value is the current time.
> End time
M
The end time point of predictive validity.
Reporting requirements
O
It describes the requirements for analytics reporting. This requirement may include e.g. the type and frequency of reporting (periodic or event triggered), the reporting periodicity in case of periodic, and reporting thresholds. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.3.3.3 Slice-specific performance analytics subscription response | Table 8.3.3.3-1 describes information elements for the slice-specific performance analytics subscription response from the ADAE server to the consumer (VAL/NSCE server).
Table 8.3.3.3-1: Slice-specific performance analytics subscription response
Information element
Status
Description
Result
M
The result of the analytics subscription request (positive or negative acknowledgement). |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.3.3.4 Slice-specific performance analytics notification | Table 8.3.3.4-1 describes information elements for the slice-specific performance analytics notification from the ADAE server to the Consumer.
Table 8.3.3.4-1: Slice-specific performance analytics notification
Information element
Status
Description
Analytics ID
O
The identifier of the analytics event. This ID can be for example “slice-specific application performance analytics”.
Analytics Output
M
The predictive or statistical parameter on performance for the target VAL application/server, with the target slice or slice instance (e.g. the min/average/max predicted RTT / end to end latency for the VAL application/server if this server uses a given slice/NSI (or for a list of given slices) in the area of interest).
Confidence level
O
(NOTE)
For predictive analytics, the achieved confidence level.
Time horizon
O
(NOTE)
The time horizon for predictive analytics.
> Start time
O
The start time point of predictive validity. If omitted, the default value is the current time.
> End time
M
The end time point of predictive validity.
NOTE: These information elements shall be provided for the predictive analytics. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.4 Procedure on support for UE-to-UE application performance analytics | |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.4.1 General | This clause describes the procedure for supporting UE-to-UE application performance analytics. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.4.2 Procedure | Figure 8.4.2-1 illustrates the procedure where the VAL session performance analytics are performed based on data collected from the ongoing VAL UE-to-UE sessions.
Pre-conditions:
1. ADAECs are connected to ADAES.
Figure 8.4.2-1: ADAES support for UE-to-UE application performance analytics
1. The consumer of the ADAES analytics service sends a subscription request to ADAES and provides the analytics event ID e.g. "UE-to-UE session performance analytics", the target VAL UE ID or group of UE IDs, the VAL service ID, the time validity and area of the request, the required confidence level, exposure level for providing UE to UE analytics. Such request can also include whether the analytics notification shall be periodic or based on an expected application QoS change (in that case also the thresholds can be provided at the request)
2. The ADAES sends a subscription response as an ACK to the consumer.
3. The ADAES selects the corresponding ADAEC #1 of the VAL UE 1 where the session performance analytics need to be performed. Such UE can be for example a capable and authorized UE from the involved VAL UE(s) within the service or group, e.g. a group lead.
4. The ADAES sends a UE-to-UE analytics request to the ADAEC #1 with the analytics ID e.g. "UE-to-UE analytics" and the configuration of the reporting required (e.g., periodic, event triggered based on threshold(s)). Such request also includes the application QoS attributes to be analyzed (latency, bitrate, jitter, application layer PER). A session starts between the VAL UE #1 and a VAL UE #2 (or more VAL UEs).
5. The ADAEC #1 starts collecting data from the corresponding VAL UE(s) based on the request. Such data can be about the latency, throughput, jitter, QoE measurements, PQI load, etc. The data can be collected by ADAEC #1 from other ADAECs via ADAE-C interface, or from the VAL clients (VAL client to VAL client interaction is out of scope).
6. The ADAEC either detects or predicts an application QoS change (depending on the authorization of ADAEC to perform analytics). Such change can be for example an application QoS downgrade related to the UE-to-UE session latency, or the application layer PER/channel losses higher than a predefined threshold, for a given time horizon with a certain confidence level.
7. The ADAEC sends the analytics to the ADAES in a UE-to-UE analytics response message.
8. The ADAES based on the received response, confirms/verifies the analytics received or provides analytics (in case that data were reported) for the UE-to-UE session. Such analytics can be about predicting the application QoS change for the UE-to-UE session.
9. The ADAES sends the derived analytics notification to the consumer.
NOTE: The mechanism for analytics collection from the UE side (steps 4, 7) shall align with the SA4 mechanism for generic data collection from the UE (TS 26.531 [3]). |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.4.3 Information flows | |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.4.3.1 General | The following information flows are specified for UE-to-UE session performance analytics based on 8.4.2 |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.4.3.2 UE-to-UE session performance analytics subscription request | Table 8.4.3.2-1 describes information elements for the UE-to-UE session performance analytics subscription request from the consumer (VAL server) to the ADAE server.
Table 8.4.3.2-1: UE-to-UE session performance analytics subscription request
Information element
Status
Description
VAL server ID
M
The identifier of the analytics consumer (VAL server).
Analytics ID
O
The identifier of the analytics event. This ID can be equivalent to “UE-to-UE session performance analytics”.
Analytics type
M
The type of analytics for the event, e.g. statistics or predictions.
Analyitcs category
M
The category of analytics for the event, e.g. performance change, performance sustainability for given QoS parameters (e.g., latency, PER, bitrate, jitter), or both.
VAL UE ID(s) and address(es)
M
The VAL UE identifier(s) and IP address(es) for which the analytics subscription applies.
VAL service ID
O
The identifier of the VAL service for which the subscription applies.
Preferred confidence level
O
The required level of accuracy for the analytics service (in case of prediction).
Area of Interest
O
The geographical or service area for which the subscription request applies.
Time validity
O
The time validity of the subscription request.
Exposure level requirement
O
The level of exposure requirement (e.g. condition on providing the analytics like threshold is reached) for the analytics to be exposed.
Reporting requirements
O
It describes the requirements for analytics reporting. This requirement may include e.g. the type and frequency of reporting (periodic or event triggered (e.g. based on an expected application QoS change) with the reporting granularity (e.g. individual session or group of sessions), the reporting periodicity in case of periodic, and reporting thresholds in case of event triggered. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.4.3.3 UE-to-UE session performance analytics subscription response | Table 8.4.3.3-1 describes information elements for the UE-to-UE session performance analytics subscription response from the ADAE server to the VAL server.
Table 8.4.3.3-1: UE-to-UE session performance analytics subscription response
Information element
Status
Description
Result
M
The result of the analytics subscription request (positive or negative acknowledgement). |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.4.3.4 UE-to-UE analytics request | Table 8.4.3.4-1 describes information elements for the UE-to-UE analytics request from the ADAE server to the ADAE client.
Table 8.4.3.4-1: UE-to-UE analytics request
Information element
Status
Description
ADAE server ID
M
The identifier of the ADAE server.
Analytics ID
O
The identifier of the analytics event (Analytics ID= UE-to-UE analytics’).
VAL UE ID(s) and address(es)
M
The VAL UE identifier(s) and IP address(es) for which the data/analytics apply.
Application QoS attributes
M
The QoS attributes (latency, bitrate, jitter, application layer PER) to be analyzed at the ADAE client.
Reporting configuration
O
The configuration for analytics reporting. This requirement may include e.g. the frequency of reporting (periodic or event triggered), the reporting periodicity in case of periodic, and reporting thresholds in case of event triggered, whether data abstraction is needed or not.
Data collection requirements
O
The requirements for data collection, including the format of data, frequency of reporting, level of abstraction of data, level of accuracy of data.
Area of Interest
O
The geographical or service area for which the request applies.
Time validity
O
The time validity of the request. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.4.3.5 UE-to-UE analytics response | Table 8.4.3.5-1 describes information elements for the UE-to-UE analytics response from the ADAE client to the ADAE server.
Table 8.4.3.5-1: UE-to-UE analytics response
Information element
Status
Description
Analytics ID
M
The identifier of the analytics event.
VAL UE ID(s) and address(es)
M
The VAL UE identifier(s) and IP address(es) for which the analytics apply.
Analytics Output
M
The reported analytics for the UE to UE sessions, which can be in form of offline stats/historical data or predictions on the requested QoS parameter based on the analytics event. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.4.3.6 ADAE Analytics Notification | Table 8.4.3.6-1 describes information elements for the ADAE Analytics Notification from the ADAE server to the consumer (VAL server).
Table 8.4.3.6-1: ADAE Analytics notification
Information element
Status
Description
Analytics ID
O
The identifier of the analytics event. This ID can be “UE-to-UE session performance analytics”.
Analytics Output
M
The analytics outputs, which can be predictive or statistical parameter.
> Performance change
O
(NOTE)
A VAL UE to UE session predicted or expected performance change.
>> Time for change
M
The predicted or expected time when the performance change happens.
>> Confidence level
O
The achieved confidence level for the predictive analytics.
> Performance sustainability
O
(NOTE)
A VAL UE to UE session performance sustainability over a given time horizon/area.
>> Time horizon
M
The time horizon for predictive analytics.
>>> Start time
O
The start time point of predictive validity. If omitted, the default value is the current time.
>>> End time
M
The end time point of predictive validity.
>> Applicable area
M
The service area or geographical area for which the analytics output applies to.
>> Confidence level
O
For predictive analytics, the achieved confidence level can be provided.
NOTE: At least one of the IEs shall be present based on the Analytics category IE provided in the subscription request. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.5 Procedure on support for location accuracy analytics | |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.5.1 General | This clause describes the procedure for supporting location accuracy analytics. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.5.2 Procedure | Figure 8.5.2-1 illustrates the procedure for location accuracy analytics enablement solution.
Pre-conditions:
1. ADAES is connected to A-ADRF.
2. ADAES has discovered SEAL LMS or FLS.
Figure 8.5.2-1: Location accuracy analytics procedure
1. The VAL server makes a subscription request to ADAE server for location accuracy prediction/stats, including an analytics event ID (e.g. "location accuracy prediction" or "location accuracy sustainability"), an analytics request type (if not identified specifically at the event ID) which can be the location accuracy prediction for a given location X and/or for a given UE/app. The request may include also the target area, a target VAL service, or a VAL UE, or group of UEs of the VAL service, time validity, accuracy threshold and requirements. If the VAL UEs are provided by the VAL server, this request may also include the expected route or a set of waypoints for the UEs of the VAL application.
2. The ADAE server sends a location accuracy analytics subscription response as an ACK to the VAL server.
3. The ADAE server discovers and maps the Data Sources with the respective analytics event ID for collecting location data for the corresponding VAL UEs or VAL service area.
4. The ADAE server subscribes for NWDAF UE mobility analytics per VAL UE (for all the VAL UEs) and gets notification on the per UE location/mobility analytics based on TS 23.288 clause 6.7.2. Such analytics may be requested for a list of waypoints per UE route (if indicated at step 1). The ADAE server subscribes also for SEAL LMS location reports for the respective VAL UEs or location reports from all VAL UEs within the requested area.
5. The ADAE server optionally requests location accuracy historical analytics /data from A-ADRF for the corresponding VAL UEs or VAL service area.
6. Based on the request, the ADAE server receives location accuracy historical analytics /data from A-ADRF for the corresponding VAL UEs or VAL service area.
7. The ADAE server abstracts or correlates the data/analytics from steps 4-6 and provides analytics on the location accuracy for the target VAL application. Depending on the event ID in step 1, the ADAE server can indicate whether the location accuracy is sustainable or is predicted to be downgraded or can be upgraded and become more granular (e.g. from meter to decimetre).
8. The ADAE server sends the location accuracy analytics notification to the consumer. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.5.3 Information flows | |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.5.3.1 General | The following information flows are specified for location accuracy analytics based on 8.5.2 |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.5.3.2 Location accuracy analytics subscription request | Table 8.5.3.2-1 describes information elements for the location accuracy analytics subscription request from the VAL server to the ADAE server.
Table 8.5.3.2-1: Location accuracy analytics subscription request
Information element
Status
Description
VAL server ID
M
The identifier of the VAL server.
Analytics ID
M
The identifier of the location accuracy analytics event. This ID can be for example "location accuracy prediction" or "location accuracy sustainability" depending on the expected outcome.
Analytics type
M
The type of analytics for the event, e.g. statistics or predictions.
VAL UE ID(s) or Group ID
M
The identity of the VAL UE(s) or group of UEs for which the analytics subscription applies
VAL service ID
O
The identifier of the VAL service for which location accuracy analytics is requested.
Location accuracy requirements
M
The accuracy threshold and VAL requirements.
Preferred confidence level
O
The level of accuracy for the analytics service (in case of prediction).
Area of Interest
O
The geographical or service area for which the subscription request applies.
Time validity
O
The time validity of the subscription request.
UE mobility / route information
O
Information on the target UE or group UE mobility including the expected route/set of waypoints.
Reporting requirements
O
It describes the requirements for analytics reporting. This requirement may include e.g. the type and frequency of reporting (periodic or event triggered), the reporting periodicity in case of periodic, and reporting thresholds. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.5.3.3 Location accuracy analytics subscription response | Table 8.5.3.3-1 describes information elements for the location accuracy analytics subscription response from the ADAE server to the VAL server.
Table 8.5.3.3-1: Location accuracy analytics subscription response
Information element
Status
Description
Result
M
The result of the analytics subscription request (positive or negative acknowledgement) |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.5.3.4 Location accuracy data request | Table 8.5.3.4-1 describes information elements for the location accuracy data request from the ADAE server to the A-ADRF.
Table 8.5.3.4-1: Location accuracy data request
Information element
Status
Description
ADAE server ID
M
The identifier of the ADAE server
Analytics ID
M
The identifier of the analytics event
List of VAL UE IDs and addresses
M
The VAL UE(s) identifiers and IP address(es) for which the data/analytics apply
VAL service ID
O
The service ID, in case of requesting historical data for a particular VAL service.
Reporting configuration
O
The configuration for data reporting. This requirement may include e.g. the frequency of reporting (periodic), the reporting periodicity in case of periodic, and reporting thresholds, whether data abstraction is needed or not.
Data collection requirements
O
The requirements for data collection, including the format of data, frequency of reporting, level of abstraction of data, level of accuracy of data.
Area of Interest
O
The geographical or service area for which the subscription request applies
Time validity
O
The time validity of the request |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.5.3.5 Location accuracy data response | Table 8.5.3.5-1 describes information elements for the location accuracy data response from the A-ADRF to the ADAE server.
Table 8.5.3.5-1: Location accuracy data response
Information element
Status
Description
Analytics ID
M
The identifier of the analytics event.
List of VAL UE IDs and addresses
M
The VAL UE(s) identifiers and IP address(es) for which the analytics apply
VAL service ID
O
The service ID, in case of requesting historical data for a particular VAL service.
Analytics Output
M
The reported analytics for the location accuracy, which can be in form of offline stats/historical data for a specific VAL service or for particular UE(s) or group of UEs |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.5.3.6 Location accuracy analytics notification | Table 8.5.3.6-1 describes information elements for the location accuracy analytics notification from the ADAE server to the VAL server.
Table 8.5.3.6-1: Location accuracy analytics notification
Information element
Status
Description
Analytics ID
M
The identifier of the analytics event.
VAL UE ID(s)
O
The identity of the VAL UE(s) for which the analytics applies.
VAL service ID
O
The identifier of the VAL service for which location accuracy analytics applies.
Analytics Output
M
The analytics outputs, which can be predictive or statistical parameter
> Location accuracy prediction
O
(see NOTE)
A predicted or expected location accuracy change (downgrade or upgrade) for a particular VAL service or UEs.
The IE shall be provided if the Analytics ID is "location accuracy prediction".
>> Applicable area
O
A list of service area or geographical area for which the analytics applies to.
>> Applicable time period
O
The time period that the analytics applies to.
>> Confidence level
O
For predictive analytics, the achieved confidence level can be provided.
> Location accuracy sustainability
O
(see NOTE)
The location accuracy sustainability for a VAL service or UE/group of UEs over a given time horizon/area.
The IE shall be provided if the Analytics ID is "location accuracy sustainability".
>> Applicable area
O
A list of service area or geographical area for which the analytics applies to.
>> Applicable time period
O
The time period that the analytics applies to.
>> Crossed reporting threshold(s)
O
The Reporting Threshold(s) that are met or exceeded or crossed by the statistics value or the expected value of the location accuracy.
>> Confidence level
O
For predictive analytics, the achieved confidence level can be provided.
NOTE: At least one of the IEs shall be present. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.6 Procedure for supporting service API analytics | |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.6.1 General | This clause describes the procedure for supporting service API analytics. Such analytics can be for one or more service APIs for a service produced by one or more service producers within the 5GS or enablement layer or the DN side (e.g., application server). |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.6.2 Procedure | Figure 8.6.2-1 illustrates the procedure for service API analytics enablement solution.
Pre-conditions:
1. ADAES acts as API management function in CAPIF
Figure 8.6.2-1: Service API analytics procedure
1. The consumer (VAL server, API provider) sends a service API event subscription request to the ADAE server to receive analytics for one or more service APIs.
2. Upon receiving the subscription request from the subscribing entity, the ADAE server checks for the relevant authorization for the event subscription. If the authorization is successful, the ADAE server stores the subscription information.
3. The ADAE server sends a service API event subscription response indicating successful subscription.
4. Upon sending the subscription response, the ADAE server requests to collect API logs to be used to derive analytics and triggers API invocation log pull request towards the CAPIF core function. The API invocation log fetch request indicates the API (or list of APIs) for which logs are required. Based on the ADAE server deployment, this can be a Query service API log request which is performed via CAPIF_Auditing API as specified in 3GPP TS 23.222 [8].
5. The CCF authorizes the request and fetches the API logs from the storage unit. CCF then sends the requested information to the ADAE server via a query service API log response.
6. The ADAES may also request service API historical analytics /data from A-ADRF for the corresponding service APIs.
7. Based on the request, the ADAES receives historical analytics/data for the service APIs from the A-ADRF.
8. The ADAE server authorizes and anonymizes the API logs (if not performed by CCF) and abstracts based on exposure level. The exposure level can be known based on pre-configuration by the OAM or based on the subscription and type of invoker. The ADAE server then derives analytics on the target service API(s) based on the logs received from the CCF. Such analytics are predictions/stats for the API status based on the analytics event.
9. The ADAE server sends the analytics as event notifications to all the subscribing entities that have subscribed for the event matching the criteria. If a notification reception information is available as part of the subscribing entity event subscription, then the notification reception information is used by the ADAE server to send event notifications to the subscribing entity. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.6.3 Information flows | |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.6.3.1 General | The following information flows are specified for service API analytics based on 8.6.2. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.6.3.2 Service API event subscription request | Table 8.6.3.2-1 describes information elements for the service API event subscription request from the consumer (VAL server, API provider) to the ADAE server.
Table 8.6.3.2-1: Service API event subscription request
Information element
Status
Description
Consumer ID
M
The information to determine the identity of the subscribing entity (consumer).
Service API information
M
The service API name or type.
Analytics ID
O
The identifier of the analytics event. This ID can be for example “service API analytics”.
Analytics type
M
The type of analytics for the event, e.g. statistics or predictions.
Criteria
M
The event criteria include event type information relevant to the prediction or stats on the number of failure API invocations, API availability, frequency and occurrence of API version changes, API location changes for the target API, etc.
Time Validity
O
Time validity of the subscription request.
Time horizon
O
The time horizon for predictive analytics.
> Start time
O
The start time point of predictive validity. If omitted, the default value is the current time.
> End time
M
The end time point of predictive validity.
Area of interest
O
Geographical or topological area for which the subscription applies.
Notification reception information
O
The information of the subscribing entity for receiving the notifications for the event.
Reporting requirements
O
It describes the requirements for analytics reporting. This requirement may include e.g. the type and frequency of reporting (periodic or event triggered), the reporting periodicity in case of periodic, and reporting thresholds in case of event triggered. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.6.3.3 Service API event subscription response | Table 8.6.3.3-1 describes information elements for the service API event subscription response to the consumer (VAL server, API provider) from the ADAE server.
Table 8.6.3.3-1: Service API event subscription response
Information element
Status
Description
Result
M
The result of the analytics subscription request (positive or negative acknowledgement). |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.6.3.4 Historical service API logs request | Table 8.6.3.4-1 describes information elements for the historical service API logs request from the ADAE server to the A-ADRF.
Table 8.6.3.4-1: Historical service API logs request
Information element
Status
Description
Service API log requestor information
M
Identity information of the originated application querying service API log request.
ADAES ID
M
Identity information of the ADAES.
Service ID or UE ID
M
Identity of the application service or UE for which the historical API invocations apply.
Target API(s) information
M
Information on target API or list of target APIs (name or type).
>Query information
O
List of query filters such as invoker's ID and IP address, service API name and version, input parameters, and invocation result.
> API aggregation abstraction flag
O
What type of aggregation or abstraction/filtering needs to be applied.
Reporting configuration
O
The configuration for the logs reporting. This requirement may include e.g. reporting thresholds, whether data abstraction is needed or not.
Area of validity
O
The geographical area for which the request applies.
Time validity
O
The time validity for the request.
Exposure level requirement
O
The level of exposure requirement (e.g. permissions on the logs like read/write/delete) for the logs to be exposed. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.6.3.5 Historical service API logs response | Table 8.6.3.5-1 describes information elements for the historical service API logs response to the ADAE server from the A-ADRF.
Table 8.6.3.5-1: Historical service API logs response
Information element
Status
Description
Result
M
Identity information of the originated application querying service API log request.
VAL service ID or UE ID
M
Identity of the application service or UE for which the API invocations apply.
Target API (s) information
M
The target service API name or type.
>Target API(s) logs
M
The API logs based on the subscription event. This may include the number of failure API invocations, API availability, frequency and occurrence of API version changes, API location changes for the target API, API throttling events, number of API invocations for a given area and time etc.
>Reporting info
O
The time and area for which the reporting applies. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.6.3.6 Service API analytics notification | Table 8.6.3.6-1 describes information elements for the service API analytics notification to the subscriber/consumer from the ADAE server.
Table 8.6.3.6-1: Service API analytics notification
Information element
Status
Description
Service API information
M
The service API name or type for which analytics apply.
Analytics ID
O
The identifier of the analytics event. This ID can be for example “service API analytics”.
Analytics Output
M
Stats or predictions based on abstracted or anonymized API logs (for example number of failure API invocations, API availability, frequency and occurrence of API version changes, API location changes for the target API, API throttling events, number of API invocations for a given area and time, API load statistics for a given edge network, etc).
Confidence level
O
For predictive analytics, the achieved confidence level can be provided.
Area of validity
O
Geographical or topological area for which the analytics apply. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.7 Slice usage pattern analytics | |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.7.1 General | This clause provides a procedure for network slice usage pattern analytics based on collected network slice performance and analytics, historical network slice status, and network performance. The analytics consumer can be either the VAL server or other analytics consumers such as SEAL NSCE server. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.7.2 Procedure on slice usage pattern analytics | Figure 8.7.2-1 illustrates the procedure for network slice usage pattern analytics.
Pre-conditions:
1. The ADAES is registered and capable of interacting with 5GS to collected network slice data.
Figure 8.7.2-1: Procedure for network slice usage pattern analytics
1. The analytics consumer (VAL server/NSCE server) sends a slice usage pattern analytics subscription request to ADAES and provides the target S-NSSAI, DNN, area of the interest, interest time period of the historical data (e.g., last year), the required confidence level, etc. Optionally, the slice requirement could also be provided.
2. The ADAES sends a slice usage pattern analytics subscription response to the analytics consumer.
3. The ADAES subscribes to the Data Sources with the respective Data Collection Event ID and the requirement for data collection related to the request slice(s). Such requests can be sent to OAM, NWDAF or the combination of them.
4. Based on subscription, the ADAES may receive Network slice related Observed Service experience statistics, Load level information of a Network Slice from NWDAF (or via NEF) as defined in TS 23.288 [4].
5. Based on subscription, the ADAES may receive Network slice / NSI related performance data from OAM as defined in TS 28.552 [7] and the alarms of network slice instances from OAM system via the procedures defined in clause 6.1 of TS 28.545 [12].
6. If the data is collected from multiple sources, the ADAES combines or correlates the data/analytics from steps 3-5 and stores the data into A-ADRF if needed.
7. The ADAES server sends the network slice data retrieval request to collect the historical data from A-ADRF.
8. The A-ADRF provides network slice historical data to the ADAES.
9. The ADAES analyzes the network slice usage pattern based on the network slice historical data and collected slice performance. When the stored historical data does not cover the required interest time period of the historical data, ADAES analyzes the slice usage pattern based on the existing stored historical data.
10. The ADAES sends the slice usage pattern analytics notification to the analytics consumer. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.7.3 Procedure on retrieving slice usage statistics data | In the procedure shown in Figure 8.7.3-1, a mechanism is provided to allow for vertical/ASP using VAL server, NSCE server to initiate request for retrieving of statistics data and receive all the historical data for a specific time window.
Pre-conditions:
1. Enterprise hosting the VAL server or NSCE server has SLA for analytics services with ADAES service provider.
2. The VAL server or NSCE server has subscribed to slice usage patterns analytics from ADAES, and statistics are available.
3. The VAL server or NSCE server has identified there is specific statistics data needed in a specific time window.
Figure 8.7.3-1: Retrieving of slice usage statistics data procedure
1. The VAL server/NSCE server sends to ADAES server a slice usage statistics data request containing information about specific time and needed statistics parameters.
2. ADAES server, based on the input in step 1, determines the needed analytics ID and data producer IDs, slice metrics for a specific slice area and specific period of time and uses the network slice data retrieval request to request the needed data from the A-ADRF.
3. A-ADRF sends back the network slice data retrieval response with the required information from its database.
4. The ADAES sends slice usage statistics data response to VAL server/NSCE server. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.7.4 Information flows | |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.7.4.1 General | The following information flows are specified for network slice usage pattern analytics based on 8.7.2. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.7.4.2 Network slice usage pattern analytics subscription request | Table 8.7.4.2-1 describes information elements for the network slice usage pattern analytics subscription request from the analytics consumer (VAL server / NSCE server) to the ADAE server.
Table 8.7.4.2-1: Network slice usage pattern analytics subscription request
Information element
Status
Description
Consumer ID
M
The identifier of the analytics consumer
Analytics ID
O
The identifier of the analytics event. This ID can be for example “Network slice usage pattern analytics”.
Analytics type
M
The type of analytics for the event, e.g. statistics or predictions.
Analytics filter information
M
Filter information for the analytics event.
>Slice identifier
M
The identifier of the target slice or slice instance, i.e. S-NSSAI.
>Slice requirement
O
The requirement of network requirements or updated requirements when the network slice was created. The GST defined by GSMA (see clause 2.2 in [10]) and the performance requirements defined in clause 7 of TS 22.261 [11] are all considered as input for the network slice related requirements.
>DNN
O
The target DNN for which the request applies.
>Target VAL UE ID(s)
O
The VAL UE(s) for which the analytics subscription applies
>Target VAL server ID
O
If consumer is different from the VAL server, this identifier shows the target VAL server for which the analytics subscription applies.
>Area of Interest
O
The geographical or service area for which the subscription request applies.
Preferred confidence level
O
The level of accuracy for the analytics service (in case of prediction.
Time validity
O
The time validity of the request.
Interest time period of the historical data
O
Interest time period of the historical data (e.g. last year),
Reporting requirements
O
It describes the requirements for analytics reporting. This requirement may include e.g. the type and frequency of reporting (periodic or event triggered), the reporting periodicity in case of periodic, and reporting thresholds in case of event triggered. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.7.4.3 Network slice usage pattern analytics subscription response | Table 8.7.4.3-1 describes information elements for the Network slice usage pattern analytics subscription response from the ADAE server to the analytics consumer (VAL/NSCE server).
Table 8.7.4.3-1: Network slice usage pattern analytics subscription response
Information element
Status
Description
Successful response (NOTE)
O
Indicates that the request was successful.
Failure response (NOTE)
O
Indicates that the request failed.
> Cause
O
Indicates the cause of request failure.
NOTE: One of these IEs shall be present in the message. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.7.4.4 Network slice usage pattern analytics notification | Table 8.7.4.4-1 describes information elements for the network slice usage pattern analytics notification from the ADAE server to the analytics Consumer.
Table 8.7.4.4-1: Network slice usage pattern analytics notification
Information element
Status
Description
Analytics ID
O
The identifier of the analytics event. This ID can be for example “Network slice usage pattern analytics”.
Analytics Output
M
The predictive or statistical parameter, which can be analytics of network slice usage pattern (e.g. periodicity of slice usage peak).
Confidence level
O
For predictive analytics, the achieved confidence level can be provided. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.7.4.5 Network slice data retrieval request | Table 8.7.4.5-1 describes information elements for the Network slice data retrieval request from the ADAE server to the A-ADRF.
Table 8.7.4.5-1: Network slice data retrieval request
Information element
Status
Description
ADAE server ID
M
The identifier of the ADAE server.
Data Collection Event ID
M
The identifier of the data collection event.
Network slice identifier
M
The identifier of the interested network slice.
VAL service ID
O
The identifier of the VAL service which is associated with network slice.
Data Collection requirements
M
The requirements for data collection, including the format of data, frequency of reporting, level of abstraction of data, level of accuracy of data.
Analytics ID
O
The identifier of the analytics event, for which the data collection is needed.
List of Data Producer IDs
O
In case when this request is performed via A-DCCF, then the list of Data Producer IDs is needed.
Target VAL UE ID(s) and address(es)
O
The VAL UE(s) identifiers and IP address(es) for which the data collection subscription apply.
Target VAL server ID
O
This identifier of the target VAL server for which the data collection subscription applies.
Area of Interest
O
The geographical or service area for which the requirement request applies.
Interest time period of the historical data
O
Interest time period of the historical data.
Time validity
O
The time validity of the request. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.7.4.6 Network slice data retrieval response | Table 8.7.4.6-1 describes information elements for the Network slice data retrieval response from the A-ADRF to the ADAE server.
Table 8.7.4.6-1: Network slice data retrieval response
Information element
Status
Description
Data Collection Event ID
M
The result of the data collection subscription request (positive or negative acknowledgement).
Network slice identifier
M
The identifier of the interested network slice
Target VAL UE ID(s) and address(es)
O (NOTE)
The VAL UE(s) identifiers and IP address(es) for which the data apply.
Target VAL server ID
O (NOTE)
This identifier of the target VAL server for which the data applies.
Analytics ID
O
The identifier of the analytics event.
Data Type
O
The type of reported data samples which can be UE data, network data, application data, edge data, or different granularities / abstraction of data (e.g. real time, non real time).
Data Output
M
The reported data, which can be inform of measurements or offline/historical data on the requested parameter (e.g. RTT deviation) based on subscription.
Timestamp
O
Time stamp of the collected report data.
NOTE: One of these shall be present based on the data collection event. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.7.4.7 Slice usage statistics data request | Table 8.7.4.7-1 describe information elements for the slice usage statistics data request between the VAL server, NSCE server and the ADAE server.
Table 8.7.4.7-1: Slice usage statistics data request
Information element
Status
Description
Consumer ID
M
The identifier of the statistics consumer.
Slice usage statistics data ID
M
Identifier of the slice usage data statistics, for which the data collection is needed.
Statistics data filter information
M
Filter information for the statistics data event.
> VAL service ID
M
Identifier of the VAL service for which the request applies.
> Network slice Identifier(s)
M
Identifier(s) of the network slice for which the request applies.
> Network slice related parameters
O
Slice parameters statistics needed.
>DNN
O
The target DNN for which the request applies.
> UE(s) related Identifier(s)
O
Identifier(s) of the related UE(s).
Area of Interest
O
The geographical or service area for which the request applies.
StartTime
M
The start time point of the requested statistics data.
EndTime
M
The end time point of the requested statistics data. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.7.4.8 Slice usage statistics data response | Table 8.7.4.8-1- describe information elements for the slice usage statistics data response between the VAL server, NSCE server and the ADAE server.
Table 8.7.4.8-1: Slice usage statistics data response
Information element
Status
Description
Result
M
Indicates the success or failure of slice usage pattern statistics data request.
Slice usage statistics data ID
M
Identifier of the slice usage data statistics.
Network slice identifier
M
The identifier of the interested network slice.
>Data output
O
(NOTE 1)
The reported data related to the network slice usage pattern statistics data request.
>> Timestamp
O
Time stamp of the collected report data.
>Cause
O
(NOTE 2)
Indicates the cause of the slice usage pattern statistics data request failure.
NOTE 1: Shall be present if the result is success.
NOTE 2: Shall be present if the result is failure. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.8 Procedure for supporting edge load analytics | |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.8.1 General | This clause describes two procedures (covering both subscribe-notify and request-response models in 8.8.2.1 and 8.8.2.2 respectively) for supporting edge load analytics, where the edge analytics are performed based on data collected from the EDN (EAS and/or EES) and A-ADRF. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.8.2 Procedure | |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.8.2.1 Subscribe-notify model | Figure 8.8.2.1-1 illustrates the procedure for edge load analytics enablement solution.
Pre-conditions:
1. ADAES has discovered the APIs to access the edge services at EDN.
2. ADAES has subscribed to OAM and NWDAF for receiving management and DN performance analytics respectively.
3. Data producers (e.g. A-ADRF, EAS, EES) may be pre-configured with data producer profiles (as in Table 8.2.4.8-1) for the data they can provide. ADAES and ADAEC have discovered available data producers and their data producer profiles.
Figure 8.8.2.1-1: ADAES support for edge analytics
1. The consumer of the ADAES analytics service sends an edge analytics subscription request to ADAES.
2. The ADAES sends an edge analytics subscription response as an ACK to the analytics consumer.
3. The ADAES maps the analytics event ID to a list of data collection event identifiers, and a list of data producer IDs. Such mapping may be preconfigured by OAM or may be determined by ADAES based on the analytics event ID and/or data producer profile (Table 8.2.4.8-1). Such Data Producers can be EASs onboarded to EDN, EESs, A-ADRF, as well as MEC Platform services.
4. The ADAES sends a subscription request to the Data Producers (EASs onboarded to EDN, EESs, A-ADRF, ADAEC) or the A-DCCF with the respective Data Collection Event ID and the requirement for data collection.
5. The Data Producers (e.g., EASs onboarded to EDN, EESs, A-ADRF, ADAEC) or the A-DCCF send a subscription response as a positive or negative acknowledgement to the ADAES.
6. The ADAES based on subscription receive offline stats/data on the edge DN load based on the analytics/data collection event ID from A-ADRF. Such stats can be about the load in terms of number of EAS or EES connections for a given area or time window, or the average edge computational resource usage or usage ratio based on the EDN total resource availability, EDN overload/high load indication events, probability of EAS/EES unavailability due to high load, etc.
7. The Data Producers at the edge start collecting data from the data generating entities. Such data can be measurements or analytics based on the data source/producer, as follows:
- from OAM or EAS/ASP (for EAS load info): Per EAS/EES computational resource load, number of connections per EES/EAS
- from N6 endpoint: N6 load
- from 5GC / NWDAF: DN performance analytics
- from OAM / MDAS: UPF load analytics (per DNAI)
- from MEC platform services (e.g., RNIS): per cell radio conditions / load for all cells within EDN coverage
NOTE 1: How the ADAES obtains the EAS load information from EAS/ASP is up to implementation.
NOTE 2: Steps 6 and 7 are not necessarily sequential and can be performed in parallel or in different order.
8. If in step 4 ADAES sent a subscription request to ADAEC as Data Producer, data collection is initiated by ADAEC from UE data generating entities.
NOTE 3: Data collection at the UE reuses the SA4 mechanism based on EVEX study (TS 26.531 [3]).
9. The edge Data Producers (targets of the subscription requests in step 4) send the data to the ADAES (based on step 7 measurements or analytics) as a data notification message. Such data can be about the load in terms of number of EAS or EES connections for a given area or time window, or the average edge computational resource usage or usage ratio based on the EDN total resource availability, EDN overload/high load indication events, probability of EAS/EES unavailability due to high load, etc.
10. ADAEC sends data (periodically or if a threshold is reached based on configuration) about the edge load as collected at the UE, e.g. in terms of number of AC or EEC connections for a given UE in a given time window, number of edge service sessions, etc.
11. The ADAES derives edge analytics on EDN / DNAI load or per EES/EAS load, based on the analytics ID and type of request. The analytics are derived based on the performance analytics received per DN or load analytics per DNAI/UPF; as well as considering measurements on the computational or RAN resource load or number of connections for the EES/EASs which are active at the EDN.
12. The ADAES sends the edge analytics to the consumer, based on the request and the derived analytics in step 9. Such analytics indicate a prediction of the EDN load considering inputs from both 5GS as well as from edge platform services. Such prediction can also be in form of a recommendation for triggering an EAS relocation to a different platform. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.8.2.2 Request-response model | Figure 8.8.2.2-1 illustrates the procedure for the analytics consumer to request analytics data of the application server(s) from the ADAE server.
Figure 8.8.2.2-1: ADAES support for edge analytics
1. The analytics consumer sends a request message to the ADAE server to receive analytics data for one or more application servers. The request message includes the identity of the analytics consumer, security credential(s) for authorization and verification, identity of all the application server for which analytics data is requested, type of analytics data, time duration since when analytics data is required.
2. Upon receiving the request, the ADAE server authenticates and authorizes the analytics consumer. If the analytics consumer is authorized, the ADAE server may get the analytics by performing step 3 to 11 of clause 8.8.2.1. The ADAE server sends a response message including the statistical and predictive analytics of the edge performance/load for the edge platform or EES/EAS for the requested duration period (if the time duration is available). |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.8.3 Information flows | |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.8.3.1 General | The following information flows are specified for edge load analytics based on 8.8.2. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.8.3.2 Edge analytics subscription request | Table 8.8.3.2-1 describes information elements for the edge analytics subscription request from the VAL server / Consumer to the ADAE server.
Table 8.8.3.2-1: Edge analytics subscription request
Information element
Status
Description
Analytics Consumer ID
M
The identifier of the analytics consumer (VAL server, EAS).
Analytics ID
M
The identifier of the analytics event. This ID can be for example “Edge platform analytics”, “EES analytics”, “EAS analytics”.
Analytics type
M
The type of analytics for the event, e.g. statistics or predictions.
Destination EAS information
O (NOTE)
This identifier shows the destination EAS information including destination EAS ID and destination EAS endpoint for which the analytics subscription applies.
Destination EES information
O (NOTE)
This identifier shows the destination EES information including destination EES ID and destination EES endpoint for which the analytics subscription applies.
DNN/DNAI
O (NOTE)
DNN or DNAIs information for which the subscription applies.
Target data producer profile criteria
O
Characteristics of the data producers to be used.
Preferred confidence level
O
The level of accuracy for the analytics service (in case of prediction).
Area of Interest
O
The geographical or service area for which the subscription request applies.
Time validity
O
The time validity of the subscription request.
Reporting requirements
O
It describes the requirements for analytics reporting. This requirement may include e.g. the type and frequency of reporting (periodic or event triggered), the reporting periodicity in case of periodic, and reporting thresholds.
NOTE: At least one of these shall be present. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.8.3.3 Edge analytics subscription response | Table 8.8.3.3-1 describes information elements for the edge analytics subscription response from the ADAE server to the consumer.
Table 8.8.3.3-1: Edge analytics subscription response
Information element
Status
Description
Result
M
The result of the analytics subscription request (positive or negative acknowledgement). |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.8.3.4 Edge data collection subscription request | Table 8.8.3.4-1 describes information elements for the edge data collection subscription request from the ADAE server to the Data Producer at the EDN or the A-DCCF, or from ADAE server to ADAE client.
Table 8.8.3.4-1: Data collection subscription request
Information element
Status
Description
ADAE server ID
M
The identifier of the ADAE server
Data Collection Event ID
M
The identifier of the data collection event
Data Collection requirements
M
The requirements for data collection, including the format of data, frequency of reporting, level of abstraction of data, level of accuracy of data.
Analytics ID
O
The identifier of the analytics event, for which the data collection is needed.
List of Data Producer IDs
O
In case when this request is performed via A-DCCF, then the list of Data Producer IDs is needed.
Destination EAS information
O (NOTE)
This identifier shows the destination EAS information including destination EAS ID and destination EAS endpoint for which the analytics subscription applies.
Destination EES information
O (NOTE)
This identifier shows the destination EES information including destination EES ID and destination EES endpoint for which the analytics subscription applies.
DNN/DNAI
O (NOTE)
DNN or DNAIs information for which the subscription applies.
Target data producer profile criteria
O
Characteristics of the data producers to be used.
Area of Interest
O
The geographical or service area for which the requirement request applies.
Time validity
O
The time validity of the request.
NOTE: At least one of these shall be present. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.8.3.5 Edge data collection subscription response | Table 8.8.3.5-1 describes information elements for the Data collection subscription response from the edge Data Producer at the EDN or the A-DCCF to the ADAE server, or from ADAE client to ADAE server.
Table 8.8.3.5-1: Data collection subscription response
Information element
Status
Description
Result
M
The result of the edge data collection subscription request (positive or negative acknowledgement). |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.8.3.6 Data Notification | Table 8.8.3.6-1 describes information elements for the Data Notification from the Data Producer to the ADAE server.
Table 8.8.3.6-1: Data notification
Information element
Status
Description
Data Collection Event ID
M
The identifier of the data collection event.
Data Producer ID
M
The identity of Data Producer.
Destination EAS information
O (NOTE)
This identifier shows the destination EAS information including destination EAS ID and destination EAS endpoint for which the analytics subscription applies.
Destination EES information
O (NOTE)
This identifier shows the destination EES information including destination EES ID and destination EES endpoint for which the analytics subscription applies.
DNN/DNAI
O (NOTE)
DNN or DNAIs information for which the subscription applies.
Analytics ID
O
The identifier of the analytics event.
Data Type
M
The type of reported data samples which can be network data, application data, edge data, or different granularities / abstraction of data (e.g. real time, non-real time). This also indicates whether data are offline (from A-ADRF or not).
Data Output
M
The reported data, which can be inform of measurements or offline/historical data on the requested parameter based on subscription. Such data can be per EDN or per DNAI or per EAS/EES load statistics and edge computational resource utilization stats for a given time and area of interest.
NOTE: At least one of these shall be present based on the data collection event. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.8.3.7 Edge analytics Notification | Table 8.8.3.7-1 describes information elements for the Edge analytics Notification from the ADAE server to the VAL server / Consumer.
Table 8.8.3.7-1: Edge analytics notification
Information element
Status
Description
Analytics ID
M
The identifier of the analytics event.
Analytics Output
M
The analytics outputs, which can be predictive or statistical parameter.
> Edge platform analytics
O
(see NOTE)
Statistics/predictions of the performance/load of the EDN or the associated edge platform, such as the number of EAS or EES connections.
>> Applicable time period
O
The time period that the analytics applies to.
>> Confidence level
O
For predictive analytics, the achieved confidence level can be provided.
> EES analytics
O
(see NOTE)
Statistics/predictions of the performance/load of the EES, such as the EES unavailability.
>> Applicable time period
O
The time period that the analytics applies to.
>> Confidence level
O
For predictive analytics, the achieved confidence level can be provided.
> EAS analytics
O
(see NOTE)
Statistics/predictions of the performance/load of the EAS, such as the EAS unavailability.
>> Applicable time period
O
The time period that the analytics applies to.
>> Confidence level
O
For predictive analytics, the achieved confidence level can be provided.
NOTE: At least one of these information elements shall be provided based on the analytics ID specified in the edge analytics subscription request as in Table 8.8.3.2-1. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.8.3.8 Get analytics data request | Table 8.8.3.8-1 describes information elements for the Get analytics data request from the analytics consumer to the ADAE server.
Table 8.8.3.8-1: Get analytics data request
Information element
Status
Description
Analytics Consumer ID
M
The identifier of the analytics consumer (VAL server, EAS, EES).
Analytics ID
M
The identifier of the analytics event. This ID can be for example “Edge platform analytics”, “EES analytics”, “EAS analytics”.
Analytics type
M
The type of analytics, e.g. statistics or predictions.
Destination EASs information
O (NOTE)
This identifier provides the list of destination EASs information including destination EAS ID and destination EAS endpoint for which the analytics request applies.
Destination EESs information
O (NOTE)
This identifier provides the list of destination EESs information including destination EES ID and destination EES endpoint for which the analytics request applies.
Preferred confidence level
O
The level of accuracy for the analytics service (in case of prediction).
Time duration
O
Time duration since when analytics data is required.
NOTE: At least one of these shall be present |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.8.3.9 Get analytics data response | Table 8.8.3.9-1 describes information elements for the Get analytics data response from the ADAE server to the consumer.
Table 8.8.3.9-1: Get analytics data response
Information element
Status
Description
Result
M
The result of the analytics data request (positive or negative acknowledgement).
Analytics ID
O
The identifier of the analytics event.
Analytics Output
O
The analytics outputs, which can be predictive or statistical parameter.
> Edge platform analytics
O
(see NOTE)
Statistics/predictions of the performance/load of the EDN or the associated edge platform, such as the number of EAS or EES connections.
>> Applicable time period
O
The time period that the analytics applies to.
>> Confidence level
O
For predictive analytics, the achieved confidence level can be provided.
> EES analytics
O
(see NOTE)
Statistics/predictions of the performance/load of the EES, such as the EES unavailability.
>> Applicable time period
O
The time period that the analytics applies to.
>> Confidence level
O
For predictive analytics, the achieved confidence level can be provided.
> EAS analytics
O
(see NOTE)
Statistics/predictions of the performance/load of the EAS, such as the EAS unavailability.
>> Applicable time period
O
The time period that the analytics applies to.
>> Confidence level
O
For predictive analytics, the achieved confidence level can be provided.
NOTE: At least one of these information elements shall be provided based on the analytics ID specified in the get analytics data request as in Table 8.8.3.8-1. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.9 Procedure on Service experience to support application performance analytics | |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.9.1 General | When Application server (like VAL server) is not available to provide analytics data due to overload or any other reasons or the application server is not providing the required quality of service experience at the UE side, the ADAE server may need to rely on alternate information sources like the application clients (like VAL clients) that provide the visibility on application service status. ADAE server can use this information from the clients alone, for the predictions and share with the consumer of the analytics. This clause provides a mechanism for the ADAE client to send service experience report to the ADAE server. ADAE server upon receiving the service experience information from the UE side entities can use it for predictions of application performance analytics.
NOTE: In this solution, if DDCC client is available in the UE, ADAE server uses data collection and reporting mechanisms as defined in 3GPP TS 26.531 [3], where the ADAE client acts as a UE application and ADAE server acts as an AF from Application service provider. The indirect reporting procedure (between ADAE client and ADAE server over ADAE-UU interface) may be used when a Direct Data Collection Client is not available in the UE. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.9.2 Procedure | |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.9.2.1 Push service experience information | The ADAE client determines the service experience information based on information received from the VAL client. The service experience information includes application specific performance measurements like end-to-end response time, connection bandwidth, request rate, server availability time, etc. On request from VAL client or any other trigger conditions, the ADAE client sends the service experience report about a VAL server to the ADAE server. The ADAE client may use the direct reporting mechanism as defined in clause 5.5 of 3GPP TS 26.531 [3]. The indirect reporting procedure (between ADAE client and ADAE server over ADAE-UU interface) may be used when a Direct Data Collection Client is not available in the UE or when the ADAE server (having Indirect Data Collection Client) needs to modify the collected UE data to satisfy the requirements of its data collection and reporting configuration. The information elements as defined in clause 8.9.3.1 are used by ADAE client to send the request and clause 8.9.3.2 are used by ADAE server to send the response.
For direct reporting, if data reporting session is not available, the ADAE client creates data reporting session as specified in clause 5.4 of 3GPP TS 26.531 [3]. Once data reporting session is available, the ADAE client (acting as a UE client) sends reports to ADAE server using direct reporting method as specified in clause 5.5 of 3GPP TS 26.531 [3].
For indirect reporting, Figure 8.9.2.1-1 illustrates the procedure where the ADAE client pushes the service experience information to the ADAE server.
Figure 8.9.2.1-1: Push service experience informtion from UE
1. The ADAE client sends Push service experience request to the ADAE server. The request contains service experience report about a VAL server and includes the information elements as specified in Table 8.9.3.1-1.
2. The ADAE server sends Push service experience response to the ADAE client.
3. Upon receiving the Push service experience request from the ADAE client, the ADAE server uses the service experience report for derivation of VAL server performance analytics.
Once UE data is collected (either using direct reporting or indirect reporting), the ADAE server may take further actions based on the analysis of the report as shared by the ADAE client. A service experience information from certain UEs, can trigger the ADAE server to fetch further service experience information from other UEs. The ADAE server can use the service experience information report from other UEs to determine/predict analytics.
- If most of the UE side entities report similar service experience, then it could be the application server problem across globally.
- If only some UEs report a bad service experience, the problem could be localized among a group of UEs.
- If the bad service experience from only one UE, the problem is localized to the UE. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.9.2.2 Pull service experience information | The procedure can be initiated by the ADAE server upon receiving a service experience from an ADAE client, to fetch service experience information from other ADAE clients or upon receiving VAL server performance analytics request from application service provider (application server) or any other event that requires the ADAE server to determine the service experience data.
Figure 8.9.2.2-1: Pull service experience information from UE
1. The ADAE server sends Pull service experience information request to the ADAE client. The request contains identifier of the specific VAL server and VAL service ID, for which the service experience report is required, as mentioned in Table 8.9.3.3-1.
2. Upon receiving the Pull service experience information request from the ADAE server, the ADAE client may take user consent to send the report if the user consent is not available already.
3. The ADAE client sends the Pull service experience information response to the ADAE server. The ADAE client instructs the Direct Data Collection Client to prioritise immediate delivery of a UE data report to the Data Collection AF as specified in clause 5.5 of 3GPP TS 26.531 [3]. The service experience contains parameters as specified in Table 8.9.3.4-1.
4. The ADAE server uses the service experience report for derivation of VAL server performance analytics. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.9.2.3 Service experience information based on triggers | The ADAE server configures triggers to the ADAE client to send the service experience report using the mechanism defined in clause 5.4 of 3GPP TS 26.531 [3].
The procedure can be initiated by the ADAE server upon receiving VAL server performance analytics request from application service provider (application server). The information elements as defined in clause 8.9.3.5 are used by ADAE server to send the request and clause 8.9.3.6 are used by ADAE client to send the response. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.9.3 Information flows | |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.9.3.1 Push service experience information request | Table 8.9.3.1-1 describes information elements for the Push service experience information request from the ADAE client to the ADAE server.
Table 8.9.3.1-1: Push service experience information request
Information element
Status
Description
VAL UE ID
M
The identifier of the VAL UE.
VAL service ID
O
The identifier of the VAL service for which the service experience report applies.
VAL server ID
M
The identifier of the VAL server for which the service experience report is sent.
Timestamp
O
Time stamp of the collected report.
VAL service experience report
O
Information related to VAL service experience. It may include end-to-end response time, connection bandwidth, request rate, VAL server availability, etc. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.9.3.2 Push service experience information response | Table 8.9.3.2-1 describes information elements for the Push service experience information response from the ADAE server to the ADAE client.
Table 8.9.3.2-1: Push service experience information response
Information element
Status
Description
Result
M
Indicates success or failure of the request. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.9.3.3 Pull service experience information request | Table 8.9.3.3-1 describes information elements for the Pull service experience information request from the ADAE server to the ADAE client.
Table 8.9.3.3-1: Pull service experience information request
Information element
Status
Description
VAL server ID
M
The identifier of the VAL server for which the service experience information is requested.
VAL service ID
O
The identifier of the VAL service for which the service experience information is requested. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.9.3.4 Pull service experience information response | Table 8.9.3.4-1 describes information elements for the Pull service experience information response from the ADAE client to the ADAE server.
Table 8.9.3.4-1: Pull service experience information request response
Information element
Status
Description
Result
M
Indicates success or failure of the request.
VAL UE ID
M
The identifier of the VAL UE.
VAL service ID (NOTE)
O
The identifier of the VAL service for which the service experience report applies.
VAL Server ID
M
The identifier of the VAL server for which the service experience report is sent.
Timestamp (NOTE)
O
Time stamp of the collected report.
VAL service experience report (NOTE)
O
Information related to VAL service experience. It may include end-to-end response time, connection bandwidth, request rate, VAL server availability, etc.
NOTE: These IEs are included only if the result is success. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.9.3.5 Configure service experience report trigger request | Table 8.9.3.5-1 describes information elements for the Configure service experience report trigger request from the ADAE server to the ADAE client.
Table 8.9.3.5-1: Configure service experience report trigger request
Information element
Status
Description
VAL server specific criteria
M
List of VAL server specific criteria.
> VAL server ID
M
The identifier of the VAL server.
> Triggering Criteria
M
Information about the triggers on which the service experience is to be reported for the VAL server.
Common Triggering criteria
O
Information about the triggers (applicable to all VAL servers) on which the service experience is fetched.
Service experience measurement to monitor
O
Information about the service experience measurements which needs to be fetched and included in the report. If not present, by default end-to-end response time is measured.
Notification Target Address
O
The Notification target address (e.g. URL) where the notifications destined for the ADAE Server should be sent to. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.9.3.6 Configure service experience report trigger response | Table 8.9.3.6-1 describes information elements for the Configure service experience report trigger response from the ADAE client to the ADAE server.
Table 8.9.3.6-1: Configure service experience report trigger response
Information element
Status
Description
Result
M
Indicates success or failure of the request. |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.10 Procedure on support for analytics storage | |
20479eb37624e17cc85fa37e0dbf82f7 | 23.436 | 8.10.1 General | This clause describes two procedures for supporting data storage to A-ADRF. |
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