Séminaire R3S présenté par Francesco Bronzino, MC à ENS de Lyon et membre du labo. LIP  le 31/05/2023 à 11h00 à Palaiseau

Speaker: Francesco Bronzino MC à l’ École normale supérieure de Lyon et membre du Laboratoire de l’Informatique du Parallélisme (LIP)

When: Wednesday May 31th, 11h00 CEST

Where:  Salle 1A318 à Palaiseau, 19 Pl. Marguerite Perey, 91120 Palaiseau

Title: Network performance and operations at the age of widespread encryption 

Abstract: Applications of machine learning to networking, from performance diagnosis to security, have conventionally relied on models that are trained on offline packet traces, without regard to the limitations of existing measurement systems nor the cost of gathering, computing, and storing the corresponding input features. As a result, there remains a significant gap between the development of statistical models for network operations and their application and systemization in practice. In this talk, we explore the challenges of operationalizing machine learning models in real world networks. First, we develop new models to infer quality metrics (i.e., startup delay and resolution) for encrypted streaming video services and demonstrate the models are practical through a 16-month deployment in 66 homes. Building on the lessons learned, we design and develop Traffic Refinery, a new framework and system that enables a joint evaluation of both the conventional notions of machine learning performance (e.g., model accuracy) and the systems-level costs of different representations of network traffic. Traffic Refinery makes it possible to explore different representations for learning, balancing systems costs related to feature extraction and model training against model accuracy.

Short Bio : Francesco Bronzino is a Maître de Conférences at École normale supérieure de Lyon and at Laboratoire de l’Informatique du Parallélisme (LIP). His research interests broadly cover the Internet infrastructure and the services that populate it, focusing on how to leverage emergent technologies to engineer software systems designed to measure and improve network service performance. His work has been published in top-tier conferences in this area such as ACM Sigmetrics, IEEE/ACM SEC, and PAM. He is currently the coordinator of the ANR-NSF MINT project as well as a scientific lead for the ANR PARFAIT project. Francesco received his Ph.D. in Electrical and Computer Engineering from WINLAB at Rutgers University, working on the design of name based services for future Internet and mobile network architectures. He previously was a research scientist at Nokia Bell Labs as well as a post-doctoral fellow at Inria Paris.