New Approaches for Network Topology Optimization Using Deep Reinforcement Learning and Graph Neural Network

New Approaches for Network Topology Optimization Using Deep Reinforcement Learning and Graph Neural Network

The exponential growth in Internet-connected devices has escalated the demand for optimized network topologies to ensure high performance. Traditional optimization methods often fall short in scalability and adaptability when it comes to network topology planning. In this paper, we address the chall...

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Bibliographic Details
Main Authors: Mohammed Ali, Florent Duchesne, Ghassan Dahman, Francois Gagnon, Diala Naboulsi
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Deep reinforcement learning
graph neural networks
proximal policy optimization
tree topology
wireless network
Online Access:https://ieeexplore.ieee.org/document/11000124/
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https://ieeexplore.ieee.org/document/11000124/

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