Hybrid Approach for WDM Network Restoration: Deep Reinforcement Learning and Graph Neural Networks

Hybrid Approach for WDM Network Restoration: Deep Reinforcement Learning and Graph Neural Networks

Ensuring robust and efficient service restoration in Wavelength Division Multiplexing (WDM) networks is crucial for maintaining network reliability amidst failures caused by disasters, equipment malfunctions, or power outages. This article presents a hybrid framework that integrates Deep Reinforceme...

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Bibliographic Details
Main Authors: Isaac Ampratwum, Amiya Nayak
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Open Journal of the Computer Society
Subjects:
Deep Reinforcement learning (DRL)
graph neural networks (GNN)
WDM networks
network survivability
Online Access:https://ieeexplore.ieee.org/document/11054280/
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