GNN for Communication Networks最新论文-2023年7月

2023年开始的一个新系列，主要是整理最新发表的Graph Neural Networks for Communication Networks (GNN4COMM)相关的最新文献，按月更新。这一期一共包括10篇期刊、9篇会议和4篇预印论文，其中2篇论文提供了开源代码，希望能帮助到大家。更多的GNN4COMM相关论文可以查看我们的Github工程(https://github.com/jwwthu/GNN-Communication-Networks)。获取这些论文的全文可以在公众号回复20230731，仅供大家交流学习。欢迎转发和关注！

号外：我们正在统计国际合作交流项目需求，欢迎有意向学术交流与科研合作的老师们在公众号私信我联系。

Journal

• Chen G, Guo Y, Zeng Q, et al. A Novel Cellular Network Traffic Prediction Algorithm Based on Graph Convolution Neural Networks and Long Short-Term Memory through Extraction of Spatial-Temporal Characteristics[J]. Processes, 2023, 11(8): 2257.
  链接：
  https://www.mdpi.com/2227-9717/11/8/2257

• Cai X, Sheng J, Wang Y, et al. A Novel Opportunistic Access Algorithm Based on GCN Network in Internet of Mobile Things[J]. IEEE Internet of Things Journal, 2023.
  链接：
  https://ieeexplore.ieee.org/abstract/document/10044926/

• Chen J, Huang X, Wang Y, et al. ASTPPO: A proximal policy optimization algorithm based on the attention mechanism and spatio–temporal correlation for routing optimization in software-defined networking[J]. Peer-to-Peer Networking and Applications, 2023: 1-19.
  链接：
  https://link.springer.com/article/10.1007/s12083-023-01489-7

• Bhavanasi S S, Pappone L, Esposito F. Dealing with Changes: Resilient Routing via Graph Neural Networks and Multi-Agent Deep Reinforcement Learning[J]. IEEE Transactions on Network and Service Management, 2023.
  链接：
  https://ieeexplore.ieee.org/abstract/document/10158424/
  代码：
  https://github.com/routing-drl/main/

• Li Y, Li J, Lv Z, et al. GASTO: A Fast Adaptive Graph Learning Framework for Edge Computing empowered Task Offloading[J]. IEEE Transactions on Network and Service Management, 2023.
  链接：
  https://ieeexplore.ieee.org/abstract/document/10056394/

• Yang Y, Zhang Z, Tian Y, et al. Implementing Graph Neural Networks Over Wireless Networks via Over-the-Air Computing: A Joint Communication and Computation Framework[J]. IEEE Wireless Communications, 2023, 30(3): 62-69.
  链接：
  https://ieeexplore.ieee.org/abstract/document/10183787/

• Farreras M, Soto P, Camelo M, et al. Improving network delay predictions using GNNs[J]. Journal of Network and Systems Management, 2023, 31(4): 65.
  链接：
  https://link.springer.com/article/10.1007/s10922-023-09758-9
  代码：
  https://github.com/mfarreras/gain-gnn

• Hou J, Tao T, Lu H, et al. Intelligent Caching with Graph Neural Network-Based Deep Reinforcement Learning on SDN-Based ICN[J]. Future Internet, 2023, 15(8): 251.
  链接：
  https://www.mdpi.com/1999-5903/15/8/251

• Maroudis A C, Theodoropoulos T, Violos J, et al. Leveraging Graph Neural Networks for SLA Violation Prediction in Cloud Computing[J]. IEEE Transactions on Network and Service Management, 2023.
  链接：
  https://ieeexplore.ieee.org/abstract/document/10173672/

• Yang M, Liu G, Zhou Z, et al. Partially Observable Mean Field Multi-Agent Reinforcement Learning Based on Graph Attention Network for UAV Swarms[J]. Drones, 2023, 7(7): 476.
  链接：
  https://www.mdpi.com/2504-446X/7/7/476

Conference

• Saleem A, Raeiszadeh M, Ebrahimzadeh A, et al. A Deep Learning Approach for Root Cause Analysis in Real-Time IIoT Edge Networks[C]//NOMS 2023-2023 IEEE/IFIP Network Operations and Management Symposium. IEEE, 2023: 1-5.
  链接：
  https://ieeexplore.ieee.org/abstract/document/10154218/

• Rivera J J D, Sarwar M M S, Alam S, et al. An Intent-Based Networking mechanism: A study case for efficient path selection using Graph Neural Networks[C]//NOMS 2023-2023 IEEE/IFIP Network Operations and Management Symposium. IEEE, 2023: 1-6.
  链接：
  https://ieeexplore.ieee.org/abstract/document/10154296/

• Aykurt K, Kellerer W. Autonomous Network Management in Multi-Domain 6G Networks based on Graph Neural Networks[C]//9th IEEE International Conference on Network Softwarization (NetSoft), PhD Symposium. 2023.
  链接：
  https://ieeexplore.ieee.org/document/10175480/

• Li J, Zhou F, Li W, et al. Componentized Task Scheduling in Cloud-Edge Cooperative Scenarios Based on GNN-enhanced DRL[C]//NOMS 2023-2023 IEEE/IFIP Network Operations and Management Symposium. IEEE, 2023: 1-4.
  链接：
  https://ieeexplore.ieee.org/abstract/document/10154311/

• Moayyedi A, Ahmadi M, Salahuddin M A, et al. Generalizable GNN-based 5G RAN/MEC Slicing and Admission Control in Metropolitan Networks[C]//NOMS 2023-2023 IEEE/IFIP Network Operations and Management Symposium. IEEE, 2023: 1-9.
  链接：
  https://ieeexplore.ieee.org/abstract/document/10154291/

• Fawaz H, Houidi O, Zeghlache D, et al. Graph Convolutional Reinforcement Learning for Load Balancing and Smart Queuing[C]//2023 IFIP Networking Conference (IFIP Networking). IEEE, 2023: 1-9.
  链接：
  https://ieeexplore.ieee.org/abstract/document/10186430/

• Zhang L, Yin B, Wang Q, et al. Graph Neural Network-based Delay Prediction Model Enhanced by Network Calculus[C]//2023 IFIP Networking Conference (IFIP Networking). IEEE, 2023: 1-7.
  链接：
  https://ieeexplore.ieee.org/abstract/document/10186434/

• Chawla A, Bosneag A M, Dalgkitsis A. Graph-based Interpretable Anomaly Detection Framework for Network Slice Management in Beyond 5G Networks[C]//NOMS 2023-2023 IEEE/IFIP Network Operations and Management Symposium. IEEE, 2023: 1-6.
  链接：
  https://ieeexplore.ieee.org/abstract/document/10154357/

• Bouton M, Jeong J, Outes J, et al. Multi-agent Reinforcement Learning with Graph Q-Networks for Antenna Tuning[C]//NOMS 2023-2023 IEEE/IFIP Network Operations and Management Symposium. IEEE, 2023: 1-7.
  链接：
  https://ieeexplore.ieee.org/abstract/document/10154310/

Preprint

• Zhao M, Fink O. Dynamic Graph Attention for Anomaly Detection in Heterogeneous Sensor Networks[J]. arXiv preprint arXiv:2307.03761, 2023.
  链接：
  https://arxiv.org/abs/2307.03761

• Liu Z, Huang L, Gao Z, et al. GA-DRL: Graph Neural Network-Augmented Deep Reinforcement Learning for DAG Task Scheduling over Dynamic Vehicular Clouds[J]. arXiv preprint arXiv:2307.00777, 2023.
  链接：
  https://arxiv.org/abs/2307.00777

• Yang H, Cheng N, Sun R, et al. Knowledge-Driven Resource Allocation for D2D Networks: A WMMSE Unrolled Graph Neural Network Approach[J]. arXiv preprint arXiv:2307.05882, 2023.
  链接：
  https://arxiv.org/abs/2307.05882

• Ma M. Multi-Task Offloading via Graph Neural Networks in Heterogeneous Multi-access Edge Computing[J]. arXiv preprint arXiv:2306.10232, 2023.
  链接：
  https://arxiv.org/abs/2306.10232