Hack2022 2nd Prize

2^nd Prize Award

Virtualized mobile and edge infrastructures with OpenAPI integrations

Team

Team Pedraforca

• Rasoul Nikbakht Silab, CTTC (Centre Tecnològic de Telecomunicacions de Catalunya)
• Michail Dalgitsis, Vicomtech
• Sarang Kahvazadeh, CTTC
• Sergio Barrachina, CTTC

From Left to right: Michail Dalgitsis (Vicomtech), Bob Gazda (InterDigital/Jury)

Introduction

We propose to integrate the MEC Radio Network Information Service (RNIS) API with Amarisoft RAN and edge infrastructure.

This integration enables monitoring/control of the RAN/edge resources. In addition, we use ML-based tools for (close to) optimum resource allocation and fulfillment of different KPIs such as bandwidth and latency.

To test our idea, we deploy a private 5G network with several edge nodes, where each node hosts an AR/VR application (a virtual classroom).

This proposal provides a real-life use-case and builds an open-source library that parses the MEC APIs to a commercial/research-based RAN product, which can be used by other teams for accelerating MEC API adoption.

TBD

Experimental scenario: a MEC-enabled cloud-native 5G network with over-the-air transmissions

Infrastructure (core, edge and RAN)

The experimental scenario will consist of a 5G network spanning three domains: core (at the cloud), edge (realized as MEC), and RAN (provided by a commercial gNB). The core and edge domains will consist of virtual machines acting as commercial/consumer off-the-shelf (COTS) servers and the virtual networks to interconnect them, so to provide computation/storage and networking resources, respectively. The RAN will be realized using the Amarisoft Callbox as gNB. Figure

Kubernetes / Cloud-native

Our deployment will have a cloud-native flavor, hence both the network functions (NFs) in the core and the MEC applications running on the edge will be realized as dockerized containers. The 5G core NFs will be based on the Open5GS open-source project [1]. Remarkably, each NF will run as a separate containerized NF (CNF). To that aim, we will rely on Kubernetes for easing the orchestration of a cluster composed of the core and edge nodes. Further, in order to enable MEC capabilities, we will i) deploy UPF(s) at the edge, and ii) develop and implement a MEC platform (MEP) to pull metrics from the gNB so to provide the Radio Network Information Service (RNIS).

Integration of MEC API with Amarisoft RAN

ETSI MEC offers a plethora of open APIs to enable communication with edge and network resources. The one which is more related to interact with our 5G network implementation is the MEC012 RNIS API. Specifically, for the RAN part we will be working with a commercial solution such as the Amarisoft gNB, in which the connected users will access the MEC applications. Therefore, an integration between Amarisoft RAN and RNIS is needed. More specifically, the interaction between the user equipment or the 5G network administrators with Amarisoft is done through a proprietary WebSocket API. Thus, one of our main contributions will be to map WebSocket actions to the RNIS API, in order to extract all the appropriate information for the users and their QoS requirements.