1. Oracle Communications Networks Data Analytics Function User Guide
  2. OCNWDAF Architecture

2 OCNWDAF Architecture

This chapter describes the OCNWDAF detailed design and architecture.

2.1 Oracle Communications Networks Data Analytics Function Architecture

OCNWDAF comprises of various microservices deployed in Kubernetes based Cloud Native Environment (CNE, example: OCCNE). The environment provides some common services such as logs or metrics data collection, analysis, graphs or charts visualization, and so on. The OCNWDAF uses standard interfaces from the Service Based Architecture (SBA) to collect data through subscription or request model from other network functions.

The microservices integrate with the environment and provide the necessary data.

The OCNWDAF architecture is depicted in the diagram below:

Figure 2-1 OCNWDAF Architecture


OCNWDAF Architecture

OCNWDAF Front End

  • Collects data from 5G NFs
  • Provides the data to backend CAP4C
  • Collects the processed analytics information from CAP4C
  • Provides the analytics information to the consumer NFs and AFs

Converged Analytics Platform for Communication (CAP4C)

  • Processes data from the Front End (FE)
  • Examines streaming data in real time to enable thresholding and other uses
  • Implements OCNWDAF analytics information (Statistical, Predictive, and Abnormal Behavior)
  • Automates machine learning models
  • Provides visualization and reports

2.2 Oracle Communications Networks Data Analytics Function Design

The OCNWDAF detailed design is depicted in the diagram below:

Figure 2-2 OCNWDAF Design


OCNWDAF Design

The OCNWDAF current architecture is aligned with 3GPP Release 16 but supports some common features in Release 17 such as Slice Load Level Analytics.

OCNWDAF Front End

The Front End (FE) interacts with 5G NFs to gather information. The OCNWDAF interacts with 5G NFs through the Service Based Architecture (SBA) or Service Based Interface (SBI) as defined in 3GPP TS 23.288 and TS 29.520.

Described below are the specialized OC-NWDAF microservices:

Note:

Some common services are also described below. The common services can be used by other 5G NFs along with OCNWDAF.

Ingress Gateway

The common Ingress gateway is refined to benefit from standard functionality such as ingress connection management, TLS1.2, and OAuth2.0

Egress Gateway

The common Egress gateway is refined to benefit from standard functionality such as egress connection management, including indirect communication, TLS1.2 and OAuth2.0, retry and reroute.

Scheduler

Offers scheduling services for timed events such as periodic consumer report notifications.

Model Manager

Tracks the consumer analytics requests, timeframe and data items required within the training data set to the respective ML models. Sends requests of models to be trained to the CAP4C and tracks the ML models that CAP4C builds.

Analytics Subscription Service

Enables service consumers to subscribe or unsubscribe to different analytics from the OCNWDAF. It handles all the subscription requests from the consumers and updates or cancels the subscription requests from the consumers. The network analytics subscription service sends analytics information notifications to the NFs, AFs, and OAM when the subscribed event occurs in the network.

Analytics Information Service

This service enables consumers to request and obtain different analytics information from the OCNWDAF based on the 3GPP defined AnalyticsInfo API. This service is based on the REST API request-response model. The network analytics information service handles the request for analytics based on the AnalyticsID. The service responds to the request and provides the analytics information if the requested analytics are available.

Data Collection Service

For 3GPP 5G sources, the Data Collection service enables the OCNWDAF to retrieve data from various sources (for example, NFs such as AMF and SMF), this data is used for computation of network analytics. The Data Collection Service ensures the OCNWDAF efficiently obtains the appropriate data with the proper granularity.

The Data Collection Controller and Data Collector microservices together form the Data Collection Service of the OCNWDAF. Data is collected to generate predictive and descriptive analytics based on analyticsID. The OCNWDAF subscribes to (or cancels subscription) a Event ID (or set of Event IDs) by invoking the Nnf_EventExposure_Subscribe (or Nnf_EventExposure_Unsubscribe) service operation. If OCNWDAF subscribes to a Event ID (or set of EventIDs), the NFs notify the OCNWDAF by invoking Nnf_EventExposure_Notify service operation. For example, the NFs can notify the OCNWDAF with a event report.

  • Data Collection Control Service: This service interacts with producer NFs to manage their subscriptions. This service also monitors and updates the consumers subscription information.

  • Data Collector Service: This service receives data from the producer NFs and streams data to the CAP4C Analytics Engine.

Converged Analytics Platform for Communication (CAP4C)

The Analytics Engine (CAP4C) is the core of OCNWDAF, which supports data collection through the Front End (FE) module. The data collected is processed with the help of ML models. Predictive or descriptive data analysis is performed and data is transmitted through real-time stream processing.

Listed below are the OCNWDAF specific microservices (along with the common microservices):

  • Ingress and Egress Gateways: In the OCNWDAF FE.
  • DBTier MySQL database: Is used for general configuration, storage of microservice data (including dynamic state data) and ML models. Some specialized reports are also generated using the DBTier.
  • Time-Series database: This database stores all the time-series data used for statistical reports and ML model datasets. Supports data roll-up (such as 1 up to 5 minute samples, 5 up to 15-minute samples, 15 minutes up to an hour sample and so on), allowing the storage of much older data in an efficient manner. Allows for fast and efficient data culling.
  • Kafka: Is the internal messaging structure. It exports special measurements and events to external consumers. It also imports measurements and events from operator sources such as a messaging bus and data lake.
  • Stream Processors: Cleans, merges, and splits data as required and examines data in windows to detect threshold crossings or perform complex calculations.
  • Model Controller: Receives model generation or execution requests from the OCNWDAF FE. The Model Controller manages and directs work to the Executor pool.
  • Model Executor: Is a variable pool of resources that trains or executes models.
  • OCNWDAF Portal: Performs the following functions:
    • Manages the OCNWDAF dashboards
    • Accepts operator input for configuration
    • Observes the time-series DB to change the display according to the change in the DB
    • Provides visualization of analytics information