Inicio  /  Future Internet  /  Vol: 16 Par: 2 (2024)  /  Artículo
ARTÍCULO
TITULO

DDPG-MPCC: An Experience Driven Multipath Performance Oriented Congestion Control

Shiva Raj Pokhrel    
Jonathan Kua    
Deol Satish    
Sebnem Ozer    
Jeff Howe and Anwar Walid    

Resumen

We introduce a novel multipath data transport approach at the transport layer referred to as ?Deep Deterministic Policy Gradient for Multipath Performance-oriented Congestion Control? (DDPG-MPCC), which leverages deep reinforcement learning to enhance congestion management in multipath networks. Our method combines DDPG with online convex optimization to optimize fairness and performance in simultaneously challenging multipath internet congestion control scenarios. Through experiments by developing kernel implementation, we show how DDPG-MPCC performs compared to the state-of-the-art solutions.

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