POSMAC: Powering Up In-Network AR/CG Traffic Classification with Online Learning
Fuente:
arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Acceso en línea: | |
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| _version_ | 1866910808787648512 |
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| author | Shirmarz, Alireza Verdi, Fabio Luciano Singh, Suneet Kumar Rothenberg, Christian Esteve |
| author_facet | Shirmarz, Alireza Verdi, Fabio Luciano Singh, Suneet Kumar Rothenberg, Christian Esteve |
| contents | In this demonstration, we showcase POSMAC1, a platform designed to deploy Decision Tree (DT) and Random Forest (RF) models on the NVIDIA DOCA DPU, equipped with an ARM processor, for real-time network traffic classification. Developed specifically for Augmented Reality (AR) and Cloud Gaming (CG) traffic classification, POSMAC streamlines model evaluation, and generalization while optimizing throughput to closely match line rates. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_00671 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | POSMAC: Powering Up In-Network AR/CG Traffic Classification with Online Learning Shirmarz, Alireza Verdi, Fabio Luciano Singh, Suneet Kumar Rothenberg, Christian Esteve Networking and Internet Architecture Distributed, Parallel, and Cluster Computing In this demonstration, we showcase POSMAC1, a platform designed to deploy Decision Tree (DT) and Random Forest (RF) models on the NVIDIA DOCA DPU, equipped with an ARM processor, for real-time network traffic classification. Developed specifically for Augmented Reality (AR) and Cloud Gaming (CG) traffic classification, POSMAC streamlines model evaluation, and generalization while optimizing throughput to closely match line rates. |
| title | POSMAC: Powering Up In-Network AR/CG Traffic Classification with Online Learning |
| topic | Networking and Internet Architecture Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2502.00671 |