Optimizing Edge Gaming Slices through an Enhanced User Plane Function and Analytics in Beyond-5G Networks
Fuente:
arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866918103126900736 |
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| author | da Silva, Bruno Marques Moreira, Larissa Ferreira Rodrigues Silva, Flávio de Oliveira Moreira, Rodrigo |
| author_facet | da Silva, Bruno Marques Moreira, Larissa Ferreira Rodrigues Silva, Flávio de Oliveira Moreira, Rodrigo |
| contents | The latest generation of games and pervasive communication technologies poses challenges in service management and Service-Level Agreement compliance for mobile users. State-of-the-art edge-gaming techniques enhance throughput, reduce latency, and leverage cloud computing. However, further development of core functions such as the User Plane Function (UPF) is needed for non-intrusive user latency measurement. This paper proposes a closed-loop architecture integrating the Network Data Analytics Function (NWDAF) and UPF to estimate user latency and enhance the 5G control plane by making it latency-aware. The results show that embedding an artificial intelligence model within NWDAF enables game classification and opens new avenues for mobile edge gaming research. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_17843 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Optimizing Edge Gaming Slices through an Enhanced User Plane Function and Analytics in Beyond-5G Networks da Silva, Bruno Marques Moreira, Larissa Ferreira Rodrigues Silva, Flávio de Oliveira Moreira, Rodrigo Distributed, Parallel, and Cluster Computing The latest generation of games and pervasive communication technologies poses challenges in service management and Service-Level Agreement compliance for mobile users. State-of-the-art edge-gaming techniques enhance throughput, reduce latency, and leverage cloud computing. However, further development of core functions such as the User Plane Function (UPF) is needed for non-intrusive user latency measurement. This paper proposes a closed-loop architecture integrating the Network Data Analytics Function (NWDAF) and UPF to estimate user latency and enhance the 5G control plane by making it latency-aware. The results show that embedding an artificial intelligence model within NWDAF enables game classification and opens new avenues for mobile edge gaming research. |
| title | Optimizing Edge Gaming Slices through an Enhanced User Plane Function and Analytics in Beyond-5G Networks |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2507.17843 |