Lab 9: SLA rApp

In this lab, you will deploy a 5G Standalone (SA) network using the OpenAirInterface (OAI) RF Simulator for the gNB and the OAI minimal 5G Core (5GC).

In the second phase of the experiment, you will use the BubbleRAN rApp SDK to develop and deploy a sample rApp that sends slicing policies to the Non-RT RIC via the R1 interface. These policies are then forwarded to the Near-RT RIC over the A1 interface, where a corresponding xApp enforces the policies at the gNB via the E2 interface. This setup enables dynamic slice management and ensures Service Level Agreement (SLA) enforcement at the RAN.

open-ran.yaml

apiVersion: athena.trirematics.io/v1
kind: Network
metadata:
  name: oran
  namespace: trirematics
spec:
  slices:
    - plmn: "00101"
      dnn: internet
      network-mode: IPv4
      service-type: 1
      differentiator: 0x000001
      ipv4-range: "12.1.1.0/24"
      ipv6-range: "2001:1:2::/64"
  access:
    - name: oai-gnb
      stack: 5g-sa
      model: oai-ran/monolithic-gnb
      radio:
        device: rf-sim
      identity:
        an-id: 10
        tracking-area: 1
      cells:
        - band: n78
          arfcn: 641280
          bandwidth: 40MHz
          subcarrier-spacing: 30kHz
          tdd-config:
            period: 5ms
            dl-slots: 7
            dl-symbols: 6
            ul-slots: 2
            ul-symbols: 4
      core-networks:
        - oai-5gc.oran
      controller: ric.oran
  core:
    - name: oai-5gc
      stack: 5g-sa
      model: oai-cn/minimal
      identity:
        region: 0
        cn-group: 4
        cn-id: 5
  edge:
    - name: ric
      stack: 5g-sa
      model: mosaic5g/flexric
    - name: sdl
      stack: 5g-sa
      model: mosaic5g/xapps-sdl
  dns:
    ipv4:
      default: 8.8.8.8
      secondary: 8.8.4.4
---
apiVersion: athena.trirematics.io/v1
kind: Terminal
metadata:
  name: ue1
  namespace: trirematics
spec:
  vendor: oai
  stack: 5g-sa
  model: terminal/nr-rfsim
  preferred-access: oai-gnb.oran
  target-cores:
    - oai-5gc.oran
  identity:
    imsi: "001010000000001"
    pin: "1234"
    opc: "0xc42449363bbad02b66d16bc975d77cc1"
    key: "0xfec86ba6eb707ed08905757b1bb44b8f"
    sqn: "0xff9bb4000001"
  slice:
    dnn: internet
    network-mode: IPv4
    service-type: 1
    differentiator: 0x000001
  radio:
    bands:
      - n78
  readiness-check:
    method: ping
    target: google-ip
    interface-name: oaitun_ue0

Network Deployment

Deploy the file using the command brc install network open-ran.yaml.

tip

The initial open-ran.yaml file does not include the xApp. The xApp will be deployed automatically by the SMO at a later stage in the experiment.

Check for the status of the deployment using the command brc observe and make sure all the Elements are in the 1/1 Y state.

Please run the following command to check the UE’s throughput before any slice enforcement is applied in the network:

brc test throughput ue1 dl gateway -- -t 60

Slice Enforcement via rApp

rapp.py

from br_rapp_sdk import A1Services
from br_rapp_sdk.a1_services.a1_policy_types import *

# Initialize the A1Services
a1_services = A1Services()

# Define the policy information
policy_info = PolicyObjectInformation(
    near_rt_ric_id =NearRtRicId("ric.oran"),
    policy_type_id=PolicyTypeId("bubbleran/sla"),
    policy_object=PolicyObject(
        scope_identifier=ScopeIdentifier(
            slice_id=SliceId(
                sst=1,
                sd="000001",
                plmn_id=PlmnId(
                    mcc="001",
                    mnc="01"
                )
            ),
        ),
        policy_statements=PolicyStatements(
            policy_objectives=PolicyObjectives(
                slice_sla_objectives=SliceSlaObjectives(
                    gua_dl_thpt_per_slice=40000,
                    max_dl_thpt_per_slice=40000
                )
            )
        )
    )
)


# Print the policy information in YAML format
print("Policy Object Information: \n", policy_info.yaml())

# Apply the policy
policy_name= "slice1"
result = a1_services.apply_policy(policy_name = policy_name, policy_object = policy_info)

# Check if the operation was successful
if result.status == 'success':
    policy_id = result.data.get('policy_id')
    print(f"Policy applied successfully: {policy_id}")
else:
    print(f"Error applying policy: {result.error}")

Use the following commands to run the rApp within the cluster:

python3 ./rapp.py

danger

Make sure the BubbleRAN rApp SDK is installed in your environment. You can install it using the command pip3 install br-rapp-sdk.

danger

Run the rApp inside the cluster, and make sure your kubeconfig file is located at ~/.kube/config.

Check for the status of the deployment using the command brc observe, you should see a new xapp named sla.dynxapp-sla-ric.oran in the list of deployed xApps. Please wait until the xApp is in the 1/1 Y state, which indicates that it has been successfully deployed and is running.

Now, you can run the command below to see the throughput of the UE after the rApp enforces the slice:

brc test throughput ue1 dl gateway -- -t 60

There is a control loop between the xApp and the gNB, over the E2 interface, to maintain the requested throughput. The gNB periodically sends KPM Indication messages to the Near-RT RIC over the E2 interface. Based on these measurements, the xApp can adjust PRB by sending RC Control requests to the gNB if needed.

tip

Check the logs of the xApp using the command brc extract logs sla.dynxapp-sla-ric.oran to see the slice enforcement process.

💬 Lab Questions 💬

1. What is the difference in the roles of the xApp and rApp in this experiment?
2. Why is there a control loop between the xApp and the gNB, and what is its function in the context of SLA enforcement?
3. Draw the message flow, starting from the rApp, through the Non-RT RIC, Near-RT RIC, xApp, and down to the RAN.
4. Why is the xApp deployed by the SMO and not manually by the user? What are the benefits of this automation?
5. Extend the experiment by using two UEs in two different slices. Send two policies with different scopes and statements for SLA enforcement.