Intelligent Bandwidth Allocation for Latency Management in NG-EPON using Reinforcement Learning Methods

2020-01-21Unverified0· sign in to hype

Qi Zhou, Jingjie Zhu, Junwen Zhang, Zhensheng Jia, Bernardo Huberman, Gee-Kung Chang

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Abstract

A novel intelligent bandwidth allocation scheme in NG-EPON using reinforcement learning is proposed and demonstrated for latency management. We verify the capability of the proposed scheme under both fixed and dynamic traffic loads scenarios to achieve <1ms average latency. The RL agent demonstrates an efficient intelligent mechanism to manage the latency, which provides a promising IBA solution for the next-generation access network.

Tasks

Management reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

Intelligent Bandwidth Allocation for Latency Management in NG-EPON using Reinforcement Learning Methods

Abstract

Tasks

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