Deep Reinforcement Learning with Graph Neural Networks for Capacitated Shortest Path Tour based Service Chaining

Author:

Hara Takanori1,Sasabe Masahiro1

Affiliation:

1. Nara Institute of Science and Technology,Graduate School of Science and Technology,Ikoma,Japan,Nara 630-0192

Publisher

IEEE

Reference35 articles.

1. Fast Graph Representation Learning with PyTorch Geometric;fey;Proc of ICLR Workshop on Representation Learning on Graphs and Manifolds,2019

2. PyTorch: An Imperative Style, High-Performance Deep Learning Library;paszke;Proc of Advances in Neural Information Processing systems,2019

3. The Internet Topology Zoo

4. Impact of Processing-Resource Sharing on the Placement of Chained Virtual Network Functions

5. IBM ILOG CPLEX Optimizer,2022

Cited by 3 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. Capacitated Shortest Path Tour-Based Service Chaining Adaptive to Changes of Service Demand and Network Topology;IEEE Transactions on Network and Service Management;2024-04

2. Deep Reinforcement Learning for Network Service Recovery in Large-Scale Failures;2023 19th International Conference on Network and Service Management (CNSM);2023-10-30

3. DQN-GNN-Based User Association Approach for Wireless Networks;Mathematics;2023-10-14

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