32 citations · 162 across the 26 of their papers we have counts for
9 papers · 1 filter
A Deep Learning Perspective on Network Routing
Yarin Perry, Felipe Vieira Frujeri, Chaim Hoch +4
Routing is, arguably, the most fundamental task in computer networking, and the most extensively studied one. A key challenge for routing in real-world environments is the need to…
Pied Piper: Rethinking Internet Data Delivery
Aran Bergman, Israel Cidon, Isaac Keslassy +4
We contend that, analogously to the transition from resource-limited on-prem computing to resource-abundant cloud computing, Internet data delivery should also be adapted to a real…
Internet Congestion Control via Deep Reinforcement Learning
Nathan Jay, Noga H. Rotman, P. Brighten Godfrey +2
We present and investigate a novel and timely application domain for deep reinforcement learning (RL): Internet congestion control. Congestion control is the core networking task o…
A Machine Learning Approach to Routing
Asaf Valadarsky, Michael Schapira, Dafna Shahaf +1
Can ideas and techniques from machine learning be leveraged to automatically generate "good" routing configurations? We investigate the power of data-driven routing protocols. Our…
Lying Your Way to Better Traffic Engineering
Marco Chiesa, Gábor Rétvári, Michael Schapira
To optimize the flow of traffic in IP networks, operators do traffic engineering (TE), i.e., tune routing-protocol parameters in response to traffic demands. TE in IP networks typi…
Exploring the Limits of Static Failover Routing
Marco Chiesa, Andrei Gurtov, Aleksander Mądry +5
We present and study the Static-Routing-Resiliency problem, motivated by routing on the Internet: Given a graph , a unique destination vertex , and an integer constant ,…