3 papers
cs.LG2025
Reinforcement Learning-based Adaptive Path Selection for Programmable Networks
José Eduardo Zerna Torres, Marios Avgeris, Chrysa Papagianni +3
This work presents a proof-of-concept implementation of a distributed, in-network reinforcement learning (IN-RL) framework for adaptive path selection in programmable networks. By…
cs.NI2020
Providing In-network Support to Coflow Scheduling
Cristian Hernandez Benet, Andreas J. Kassler, Gianni Antichi +2
Many emerging distributed applications, including big data analytics, generate a number of flows that concurrently transport data across data center networks. To improve their perf…
cs.NI2019
Programmable Event Detection for In-Band Network Telemetry
Jonathan Vestin, Andreas Kassler, Deval Bhamare +3
In-Band Network Telemetry (INT) is a novel framework for collecting telemetry items and switch internal state information from the data plane at line rate. With the support of prog…