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GNNs for Routing Optimization Survey by kimzinu07 is a document available to read on EtoBox.

This paper reviews the application of graph neural networks (GNNs) in optimizing routing for next-generation communication networks, highlighting their advantages over traditional routing protocols in handling complexity and scalability. It categorizes GNN-based routing methods into supervised learning, reinforcement learning, and discusses challenges such as scalability and real-world deployment. The study aims to inspire further research and practical applications of GNNs in routing optimization across va

Author
kimzinu07
Language
EN