most citedLearning to Sail Dynamic Networks: The MARLIN Reinforcement Learning Framework for Congestion Control in Tactical Environments

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cs.LG2023★ 1 cited

Learning to Sail Dynamic Networks: The MARLIN Reinforcement Learning Framework for Congestion Control in Tactical Environments

Raffaele Galliera, Mattia Zaccarini, Alessandro Morelli +4

Conventional Congestion Control (CC) algorithms,such as TCP Cubic, struggle in tactical environments as they misinterpret packet loss and fluctuating network performance as congest…

cs.LG2023

MARLIN: Soft Actor-Critic based Reinforcement Learning for Congestion Control in Real Networks

Raffaele Galliera, Alessandro Morelli, Roberto Fronteddu +1

Fast and efficient transport protocols are the foundation of an increasingly distributed world. The burden of continuously delivering improved communication performance to support…