Cruise Control: Dynamic Model Selection for ML-Based Network Traffic Analysis
J Hugon, P Schmitt, A Busson, F Bronzino - arXiv preprint arXiv …, 2024 - arxiv.org
Modern networks increasingly rely on machine learning models for real-time insights,
including traffic classification, application quality of experience inference, and intrusion …
including traffic classification, application quality of experience inference, and intrusion …
Practical Systems For Traffic Analysis on Modern Networks
G Wan - 2024 - search.proquest.com
Network traffic analysis is essential for understanding and securing production networks. It is
routinely used by both operators and researchers to investigate network behaviors, identify …
routinely used by both operators and researchers to investigate network behaviors, identify …
Bridging the Gap Between Machine Learning and Networked Systems
F Bronzino - 2024 - hal.science
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 …
have conventionally relied on models that are trained on offline packet traces, without regard …
Machine Learning for Autonomous Vehicle Traffic Signal Prediction and Coordination
C Müller - Journal of Artificial Intelligence Research and …, 2023 - aimlstudies.co.uk
Recent research-grade literature posits developing novel traffic control policies that could
better accommodate both human-driven vehicles and CAVs [1]. In addition to the traffic …
better accommodate both human-driven vehicles and CAVs [1]. In addition to the traffic …
[PDF][PDF] Dynamic model serving for network traffic analysis
F Lyon - fbronzino.com
Network management increasingly relies on machine learning models to make predictions
for network management tasks, including traffic classification, intrusion detection, and …
for network management tasks, including traffic classification, intrusion detection, and …