Modelling and Simulation of 5G Core Plane
Cloud-native 5G is an emerging topic that is enabled by the new architecture of 5G, cloud computing and virtualization. New service-based architecture of cellular networks allows core network components to be deployed as microservices , conformant to cloud-native principles. This approach paves the way for new research to efficiently automate, scale, and verify 5G core deployments to analyze the trade-off between the deployment decisions.
NextGSim[1] is a simulator tool that was developed by our chair to simulate resource management for Beyond 5G Networks. Its main goal is to accurately model resource management algorithms in the radio and computing continuum, to efficiently allocate resources to the users with stringent Quality of Service requirements. The focus of the simulator is latency-sensitive applications, where the end-to-end delay requirement is on the order of tens of milliseconds. These latency-sensitive applications are usually deployed as microservices that form a directed-acyclic graph. The simulator models these microservices according to their processing requirements and the resources they consume.
In this thesis, the goal will be modeling the 5G core as a distributed application, where the microservices that form the 5G core are deployed and orchestrated in the edge-cloud continuum. The student is expected to analyze the network traffic and processing requirement of the 5G core functions and create a model of those using a testbed built on an open source 5G core software free5GC[2]. After the analysis, this model will be implemented in NextGSim. Afterwards, the work will be concluded with experiments that address deployment options, such as service placement, server choice and user association.
Requirements:
- Knowledge about cloud technologies
- Solid mathematical background
- Interest in cellular networks
- Experience with network simulation would be a plus.
References:
[1] A. Jano, M. M. Bese, N. Mohan, W. Kellerer and J. Ott, "next GSIM: Towards Simulating Network Resource Management for Beyond 5G Networks," 2023 IEEE Future Networks World Forum (FNWF), Baltimore, MD, USA, 2023, pp. 1-7, doi: 10.1109/FNWF58287.2023.10520638.