2025
Carlos Eduardo Menin, Igor Martins Silva, Vinícius Boff Alves, Gabriel Lando, Cristiano Bonato Both, José Marcos Silva Nogueira, Juliano Araujo Wickboldt
Explainable performance analysis of open-source 5G core network implementations via observability Inproceedings
In: 11th IEEE International Conference on Network Softwarization, NetSoft 2025, Budapest, Hungary, Jun 23-27, 2025, pp. 397-405, IEEE, 2025, ISSN: 2693-9789, (Best student paper award).
Abstract Links BibTeX Tags: 5G Microservices Network Virtualization & Slicing Observability
@inproceedings{conf/netsoft/Menin5GCore25,
title = {Explainable performance analysis of open-source 5G core network implementations via observability},
author = {Carlos Eduardo Menin and Igor Martins Silva and Vinícius Boff Alves and Gabriel Lando and Cristiano Bonato Both and José Marcos Silva Nogueira and Juliano Araujo Wickboldt},
url = {https://ieeexplore.ieee.org/abstract/document/11080540},
doi = {10.1109/NetSoft64993.2025.11080540},
issn = {2693-9789},
year = {2025},
date = {2025-06-23},
urldate = {2025-06-23},
booktitle = {11th IEEE International Conference on Network Softwarization, NetSoft 2025, Budapest, Hungary, Jun 23-27, 2025},
pages = {397-405},
publisher = {IEEE},
abstract = {The advent of fifth-generation mobile networks (5G) has brought transformative improvements in data transfer speeds, latency reduction, and device connectivity, enabled by the softwarization, virtualization, and disaggregation of network functions. Open-source projects have been instrumental in facilitating software-driven 5G deployments on standard hardware, accelerating the development of private 5G networks, test environments, and advancing research and innovation in the domain. Despite these advancements, the current maturity of open-source solutions remains inadequate for high-performance, large-scale 5G deployments. Existing 5G performance testing approaches primarily adopt a black-box perspective, which fails to capture the intricate interactions among core 5G components, thereby hindering the identification of performance bottlenecks. Additionally, testing is often limited to small-scale environments, and publicly available datasets from real-world deployments are scarce. To overcome these challenges, this paper introduces an observability-driven methodology for testing 5G core network performance, offering deeper insights into the internal interactions of network components. We contribute to research and innovation in 5G and beyond field by (i) enabling the simulation of varying user arrival rates, (ii) releasing a public dataset capturing data of 5G core components interactions, logs, and performance metrics, and (iii) providing a comparative analysis of two popular open-source 5G core implementations based on our observability-oriented methodology.},
note = {Best student paper award},
keywords = {5G, Microservices, Network Virtualization & Slicing, Observability},
pubstate = {published},
tppubtype = {inproceedings}
}
The advent of fifth-generation mobile networks (5G) has brought transformative improvements in data transfer speeds, latency reduction, and device connectivity, enabled by the softwarization, virtualization, and disaggregation of network functions. Open-source projects have been instrumental in facilitating software-driven 5G deployments on standard hardware, accelerating the development of private 5G networks, test environments, and advancing research and innovation in the domain. Despite these advancements, the current maturity of open-source solutions remains inadequate for high-performance, large-scale 5G deployments. Existing 5G performance testing approaches primarily adopt a black-box perspective, which fails to capture the intricate interactions among core 5G components, thereby hindering the identification of performance bottlenecks. Additionally, testing is often limited to small-scale environments, and publicly available datasets from real-world deployments are scarce. To overcome these challenges, this paper introduces an observability-driven methodology for testing 5G core network performance, offering deeper insights into the internal interactions of network components. We contribute to research and innovation in 5G and beyond field by (i) enabling the simulation of varying user arrival rates, (ii) releasing a public dataset capturing data of 5G core components interactions, logs, and performance metrics, and (iii) providing a comparative analysis of two popular open-source 5G core implementations based on our observability-oriented methodology.
Carlos Eduardo Menin, Igor Martins Silva, Vinícius Boff Alves, Gabriel Lando, Cristiano Bonato Both, José Marcos Silva Nogueira, Juliano Araujo Wickboldt
Enabling cloud-native observability for white-box performance analysis of the 5G core Inproceedings
In: 38th IEEE/IFIP Network Operations and Management Symposium, NOMS 2025, Honolulu, HI, USA, May 12-16, 2025, pp. 1–6, IEEE, 2025, ISSN: 2374-9709, (Experience session paper).
Abstract Links BibTeX Tags: 5G Microservices Network Virtualization & Slicing Observability
@inproceedings{conf/noms/Menin5GCore25,
title = {Enabling cloud-native observability for white-box performance analysis of the 5G core},
author = {Carlos Eduardo Menin and Igor Martins Silva and Vinícius Boff Alves and Gabriel Lando and Cristiano Bonato Both and José Marcos Silva Nogueira and Juliano Araujo Wickboldt},
url = {https://ieeexplore.ieee.org/abstract/document/11073613},
doi = {10.1109/NOMS57970.2025.11073613},
issn = {2374-9709},
year = {2025},
date = {2025-05-12},
urldate = {2025-05-12},
booktitle = {38th IEEE/IFIP Network Operations and Management Symposium, NOMS 2025, Honolulu, HI, USA, May 12-16, 2025},
pages = {1--6},
publisher = {IEEE},
abstract = {The fifth generation of mobile networks (5G) has introduced significant advancements in data transfer rates, latency, and device density, empowered by softwarization, virtualization, and disaggregation of network functions. Open-source initiatives have played a crucial role in enabling software-based 5G network deployments on commodity hardware, driving the growth of private 5G networks and testbeds, and fostering research and innovation in the field. However, the maturity level of such open-source technologies is still insufficient for highly performant large-scale deployments. Current 5G performance testing methodologies rely predominantly on a black-box approach, which overlooks the complexity of interactions between 5G core components, limiting the ability to explain performance bottlenecks. To address this limitation, this paper proposes a new observability-driven methodology for 5G core network performance testing, which improves visibility into internal component interactions. We contribute to research and innovation in 5G and beyond field by (i) implementing testing workloads that are able to simulate varying user arrival rates and (ii) integrate a set of cloud-native observability tools to allow white-box performance evaluation of the 5G core.},
note = {Experience session paper},
keywords = {5G, Microservices, Network Virtualization & Slicing, Observability},
pubstate = {published},
tppubtype = {inproceedings}
}
The fifth generation of mobile networks (5G) has introduced significant advancements in data transfer rates, latency, and device density, empowered by softwarization, virtualization, and disaggregation of network functions. Open-source initiatives have played a crucial role in enabling software-based 5G network deployments on commodity hardware, driving the growth of private 5G networks and testbeds, and fostering research and innovation in the field. However, the maturity level of such open-source technologies is still insufficient for highly performant large-scale deployments. Current 5G performance testing methodologies rely predominantly on a black-box approach, which overlooks the complexity of interactions between 5G core components, limiting the ability to explain performance bottlenecks. To address this limitation, this paper proposes a new observability-driven methodology for 5G core network performance testing, which improves visibility into internal component interactions. We contribute to research and innovation in 5G and beyond field by (i) implementing testing workloads that are able to simulate varying user arrival rates and (ii) integrate a set of cloud-native observability tools to allow white-box performance evaluation of the 5G core.