The consumer of the ADAES analytics service sends a VAL performance analytics subscription request to ADAES.

The ADAES sends a subscription response as a positive or negative acknowledgement to the consumer of the analytics service.

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.

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.

The Data Producer(s) sends a subscription response as a positive or negative acknowledgement to the ADAES.

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).

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.

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.

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.

When the VAL UE session with VAL server finishes, the ADAEC notifies the ADAES of the completion of the reporting.

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.

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.

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, whether offline/online analytics were used.

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 UE perf prediction", 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.

The ADAES sends a subscription response as an ACK to the consumer.

The ADAES selects the corresponding ADAEC of the VAL UE for which the local analytics need to be performed.

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 threshold or event).

The ADAEC sends a subscription response to ADAES.

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.

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).

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.

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.

The ADAEC filters or correlates the data based on the analytics event and the data collection configuration.

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.

The ADAEC sends the data of step 9 or the analytics of step 10 (if ADAEC performs analytics) to the ADAES.

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.

The ADAES sends the analytics to the consumer, where these analytics include the VAL UE #1 session predicted performance for a given area and time horizon, including also the confidence level, whether offline/online analytics were used.