Presentation Information
[WP-A-3]Dynamic RWA for Programmable Filterless Optical Networks Based on Deep Reinforcement Learning
Zhaoyang Liu, Taoning Zheng, Tingyi Yao, Xiangyu Ge, Yi Fang, ○Bitao Pan (Beijing Univ. of Posts and Telecommunications)
Keywords:
Artificial intelligence and machine learning for optical network design,control,and management
We propose a graph convolutional network enhanced reinforcement learning framework for dynamic resource allocation in programmable filterless optical networks. It realized 9.2% and 19% blocking rate reductions compared to two benchmarks with lower wavelength waste.