Can I read POSMAC: Powering Up In-Network AR/CG Traffic Classification with Online Learning on EtoBox?

POSMAC: Powering Up In-Network AR/CG Traffic Classification with Online Learning by Shirmarz, Alireza; Verdi, Fabio Luciano; Singh, Suneet Kumar; Rothenberg, Christian Esteve is a scholarly article available to read on EtoBox.

What is POSMAC: Powering Up In-Network AR/CG Traffic Classification with Online Learning about?

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.

Author

Shirmarz, Alireza; Verdi, Fabio Luciano; Singh, Suneet Kumar; Rothenberg, Christian Esteve

Published

2025

Language

EN