3 citations · 3 across the 7 of their papers we have counts for
7 papers
Characterizing the Impact of Active Queue Management on Speed Test Measurements
Siddhant Ray, Taveesh Sharma, Jonatas Marques +3
Present day speed test tools measure peak throughput, but often fail to capture the user-perceived responsiveness of a network connection under load. Recently, platforms such as ND…
NetSSM: Multi-Flow and State-Aware Network Trace Generation using State Space Models
Andrew Chu, Xi Jiang, Shinan Liu +4
Access to raw network traffic data is essential for many computer networking tasks, from traffic modeling to performance evaluation. Unfortunately, this data is scarce due to high…
Cruise Control: Dynamic Model Selection for ML-Based Network Traffic Analysis
Johann Hugon, Paul Schmitt, Anthony Busson +1
Modern networks increasingly rely on machine learning models for real-time insights, including traffic classification, application quality of experience inference, and intrusion de…
Feasibility of State Space Models for Network Traffic Generation
Andrew Chu, Xi Jiang, Shinan Liu +4
Many problems in computer networking rely on parsing collections of network traces (e.g., traffic prioritization, intrusion detection). Unfortunately, the availability and utility…
Beyond Data Points: Regionalizing Crowdsourced Latency Measurements
Taveesh Sharma, Paul Schmitt, Francesco Bronzino +2
Despite significant investments in access network infrastructure, universal access to high-quality Internet connectivity remains a challenge. Policymakers often rely on large-scale…
VidPlat: A Tool for Fast Crowdsourcing of Quality-of-Experience Measurements
Xu Zhang, Hanchen Li, Paul Schmitt +3
For video or web services, it is crucial to measure user-perceived quality of experience (QoE) at scale under various video quality or page loading delays. However, fast QoE measur…
NetDiffusion: Network Data Augmentation Through Protocol-Constrained Traffic Generation
Xi Jiang, Shinan Liu, Aaron Gember-Jacobson +4
Datasets of labeled network traces are essential for a multitude of machine learning (ML) tasks in networking, yet their availability is hindered by privacy and maintenance concern…