MAGNNETO: A Graph Neural Network-Based Multi-Agent System for Traffic Engineering

Author:

Bernárdez Guillermo1ORCID,Suárez-Varela José1,López Albert1,Shi Xiang2,Xiao Shihan2,Cheng Xiangle2,Barlet-Ros Pere1,Cabellos-Aparicio Albert1

Affiliation:

1. Barcelona Neural Networking Center, Universitat Politècnica de Catalunya, Barcelona, Spain

2. Network Technology Lab., Huawei Technologies Company Ltd., Beijing, China

Funder

Spanish I+D+i project TRAINER-A

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Hardware and Architecture

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Differential privacy distributed optimization algorithm against adversarial attacks for efficiency optimization of complex industrial processes;Advanced Engineering Informatics;2024-10

2. Flow-Aware Scheduling with Graph Neural Network Routing for Resource Efficiency in Time-Sensitive Networking;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

3. Fast Learning for Multi-Agent with Combination of Imitation Learning and Model-Based Learning for Formation Change of Transport Robots;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

4. Sparsifying Graph Neural Networks with Compressive Sensing;Proceedings of the Great Lakes Symposium on VLSI 2024;2024-06-12

5. A Review on Traffic Engineering Systems in Software-defined Networks using Routing Mechanisms;2024 3rd International Conference on Applied Artificial Intelligence and Computing (ICAAIC);2024-06-05

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