This is the repository for the collection of Graph-based Deep Learning for Communication Networks.

If you find this repository helpful, you may consider cite our relevant work:

• Jiang W. Graph-based Deep Learning for Communication Networks: A Survey[J]. Computer Communications, 2022, 185:40-54. Link
  • For the surveyed studies in different scenarios, you may check survey.md

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• Suárez-Varela J, Almasan P, Ferriol-Galmés M, et al. Graph Neural Networks for Communication Networks: Context, Use Cases and Opportunities[J]. IEEE Network, 2022. Link
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• Li Y, Xie S, Wan Z, et al. Graph-powered learning methods in the Internet of Things: A survey[J]. Machine Learning with Applications, 2023, 11: 100441. Link
• Dong G, Tang M, Wang Z, et al. Graph neural networks in IoT: A survey[J]. ACM Transactions on Sensor Networks, 2023, 19(2): 1-50. Link GNN4IoT Repository

• Suárez-Varela J, Ferriol-Galmés M, López A, et al. The graph neural networking challenge: a worldwide competition for education in AI/ML for networks[J]. ACM SIGCOMM Computer Communication Review, 2021, 51(3): 9-16. Link
• Ferriol-Galmés M, Suárez-Varela J, Rusek K, et al. Scaling Graph-based Deep Learning models to larger networks[J]. arXiv preprint arXiv:2110.01261, 2021. Link

• Pujol-Perich D, Suárez-Varela J, Ferriol-Galmés M, et al. IGNNITION: fast prototyping of graph neural networks for communication networks[M]//Proceedings of the SIGCOMM'21 Poster and Demo Sessions. 2021: 71-73. Link
• Pujol-Perich D, Suárez-Varela J, Ferriol M, et al. IGNNITION: Bridging the Gap Between Graph Neural Networks and Networking Systems[J]. IEEE Network, 2021. Link Code

The list would be updated monthly.

• Xu R, Wu G, Wang W, et al. Applying self-supervised learning to network intrusion detection for network flows with graph neural network[J]. Computer Networks, 2024: 110495. Link Code
• Chang L, Branco P. Embedding residuals in graph-based solutions: the E-ResSAGE and E-ResGAT algorithms. A case study in intrusion detection[J]. Applied Intelligence, 2024: 1-16. Link
• Zhang P, Wang E, Luo Z, et al. Energy-Efficient Virtual Network Embedding: A Deep Reinforcement Learning Approach Based on Graph Convolutional Networks[J]. Electronics, 2024, 13(10): 1918. Link
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• Chen Z, Ge W, Fei H, et al. A lightweight graph neural networks based enhanced separated detection scheme for downlink MIMO-SCMA systems[J]. IEICE Transactions on Communications, 2024. Link
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• Liu C, Aggarwal V, Lan T, et al. FERN: Leveraging Graph Attention Networks for Failure Evaluation and Robust Network Design[J]. IEEE/ACM Transactions on Networking, 2024. Link Code
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• He C, Li Y, Lu Y, et al. ICNet: GNN-Enabled Beamforming for MISO Interference Channels with Statistical CSI[J]. IEEE Transactions on Vehicular Technology, 2024. Link
• Zhao B, Wu J, Ma Y, et al. Meta-Learning for Wireless Communications: A Survey and a Comparison to GNNs[J]. IEEE Open Journal of the Communications Society, 2024. Link
• Liu S, Guo J, Yang C. Multidimensional graph neural networks for wireless communications[J]. IEEE Transactions on Wireless Communications, 2024. Link Data
• Du A, Jia J, Chen J, et al. Online two-timescale service placement for time-sensitive applications in MEC-assisted network: A TMAGRL approach[J]. Computer Networks, 2024, 244: 110339. Link
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• Liu M, Xu H, Sheng Q Z, et al. QoSGNN: Boosting QoS Prediction Performance with Graph Neural Networks[J]. IEEE Transactions on Services Computing, 2024. Link
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• Huang S, Wei Y, Peng L, et al. xNet: Modeling Network Performance With Graph Neural Networks[J]. IEEE/ACM Transactions on Networking, 2024. Link
• Tam P, Ros S, Song I, et al. A Survey of Intelligent End-to-End Networking Solutions: Integrating Graph Neural Networks and Deep Reinforcement Learning Approaches[J]. Electronics, 2024, 13(5): 994. Link
• Li Y, Lu Y, Ai B, et al. GNN-Enabled Max-Min Fair Beamforming[J]. IEEE Transactions on Vehicular Technology, 2024. Link
• Xia W, He D, Yu L. Locational detection of false data injection attacks in smart grids: A graph convolutional attention network approach[J]. IEEE Internet of Things Journal, 2024. Link
• Kannamma R, Umadevi K S. An efficient frame preemption algorithm for time-sensitive networks using enhanced graph convolutional network with particle swarm optimization[J]. Measurement: Sensors, 2024, 31: 100964. Link
• Huang S, Zhang H, Wang X, et al. Fine-Grained Spatio-Temporal Distribution Prediction of Mobile Content Delivery in 5G Ultra-Dense Networks[J]. IEEE Transactions on Mobile Computing, 2024. Link
• Zhao J, Tang T, Bu B, et al. Graph neural network‐based attack prediction for communication‐based train control systems[J]. CAAI Transactions on Intelligence Technology, 2024. Link
• Peng Y, Guo J, Yang C. Learning Resource Allocation Policy: Vertex-GNN or Edge-GNN?[J]. IEEE Transactions on Machine Learning in Communications and Networking, 2024. Link
• Zhao L, He C, Zhu X. A Fault Diagnosis Method for 5G Cellular Networks Based on Knowledge and Data Fusion[J]. Sensors, 2024, 24(2): 401. Link
• Ngo D T, Aouedi O, Piamrat K, et al. Empowering Digital Twin for Future Networks with Graph Neural Networks: Overview, Enabling Technologies, Challenges, and Opportunities[J]. Future Internet, 2023, 15(12): 377. Link
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• Lyu S, Peng L, Chang S Y. Investigating Large-Scale RIS-Assisted Wireless Communications Using GNN[J]. IEEE Transactions on Consumer Electronics, 2024. Link
• He J, Cheng N, Yin Z, et al. Load-Aware Network Resource Orchestration in LEO Satellite Network: A GAT-Based Approach[J]. IEEE Internet of Things Journal, 2024. Link
• Zhong L, Chen Z, Cheng H, et al. Lightweight Federated Graph Learning for Accelerating Classification Inference in UAV-assisted MEC Systems[J]. IEEE Internet of Things Journal, 2024. Link

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• Hou J, Nayak A. A Graph-Based Spatial-Temporal Deep Reinforcement Learning Model for Edge Caching[C]//GLOBECOM 2023-2023 IEEE Global Communications Conference. IEEE, 2023: 6456-6461. Link
• Hou J, Tao T, Lu H, et al. An Optimized GNN-Based Caching Scheme for SDN-Based Information-Centric Networks[C]//GLOBECOM 2023-2023 IEEE Global Communications Conference. IEEE, 2023: 401-406. Link
• Li W, Liao M, Wang X, et al. Applying Multiple-Correlations of Network to Cell Traffic Forecasting[C]//GLOBECOM 2023-2023 IEEE Global Communications Conference. IEEE, 2023: 7405-7410. Link
• Yang N, Wang S, Chen M, et al. Energy Efficient Collaborative Federated Learning Design: A Graph Neural Network based Approach[C]//GLOBECOM 2023-2023 IEEE Global Communications Conference. IEEE, 2023: 164-169. Link
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• Le H A, Van Chien T, Choi W. Graph Neural Network based Active and Passive Beamforming for Distributed STAR-RIS-Assisted Multi-User MISO Systems[J]. arXiv preprint arXiv:2405.01979, 2024. Link
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• Van Chien T, Le H A, Tung T H, et al. Joint Power Allocation and User Scheduling in Integrated Satellite-Terrestrial Cell-Free Massive MIMO IoT Systems[J]. arXiv preprint arXiv:2401.03754, 2024. Link
• Li H, Li P, Assis K D, et al. NetMind: Adaptive RAN Baseband Function Placement by GCN Encoding and Maze-solving DRL[J]. arXiv preprint arXiv:2401.06722, 2024. Link Code

• Bellili A, Kara N. A graphical deep learning technique-based VNF dependencies for multi resource requirements prediction in virtualized environments[J]. Computing, 2023: 1-25. Link
• Zhang X, Guo L, Ben C, et al. A-GCRNN: Attention graph convolution recurrent neural network for multi-band spectrum prediction[J]. IEEE Transactions on Vehicular Technology, 2023. Link Code
• Guo K, Chen J, Dong P, et al. DTFL: A Digital Twin-assisted Graph Neural Network Approach for Service Function Chains Failure Localization[J]. IEEE Transactions on Cloud Computing, 2023. Link Data
• Li B, Yang L L, Maunder R G, et al. Heterogeneous graph neural network for power allocation in multicarrier-division duplex cell-free massive MIMO systems[J]. IEEE Transactions on Wireless Communications, 2023. Link Code
• Gharib A, Ibnkahla M. User Security Oriented Information-Centric IoT Nodes Clustering With Graph Convolution Networks[J]. IEEE Internet of Things Journal, 2023. Link
• Zeng L, Chen X, Huang P, et al. Serving Graph Neural Networks With Distributed Fog Servers for Smart IoT Services[J]. IEEE/ACM Transactions on Networking, 2023. Link
• Pamuklu T, Syed A, Kennedy W S, et al. Heterogeneous GNN-RL Based Task Offloading for UAV-aided Smart Agriculture[J]. IEEE Networking Letters, 2023. Link
• Lee M, Yu G, Dai H. Privacy-preserving decentralized inference with graph neural networks in wireless networks[J]. IEEE Transactions on Wireless Communications, 2023. Link
• Wu Q, Ng B K, Lam C T, et al. Shared Graph Neural Network for Channel Decoding[J]. Applied Sciences, 2023, 13(23): 12657. Link
• Tang D, Zhang Q. UAV 5G: enabled wireless communications using enhanced deep learning for edge devices[J]. Wireless Networks, 2023: 1-14. Link
• Huang Y, Yang D, Feng B, et al. A GNN-Enabled Multipath Routing Algorithm for Spatial-Temporal Varying LEO Satellite Networks[J]. IEEE Transactions on Vehicular Technology, 2023. Link
• Lv W, Yang P, Zheng T, et al. Graph Reinforcement Learning-based Dependency-Aware Microservice Deployment in Edge Computing[J]. IEEE Internet of Things Journal, 2023. Link
• Deng L, Liu X Y, Zheng H, et al. Graph-Tensor Neural Networks for Network Traffic Data Imputation[J]. IEEE/ACM Transactions on Networking, 2023. Link Code
• Janarthanan A, Srinivasan V. Multi‐objective cluster head‐based energy aware routing using optimized auto‐metric graph neural network for secured data aggregation in Wireless Sensor Network[J]. International Journal of Communication Systems, 2023. Link
• Chen Z, Cheng G, Niu D, et al. WFF-EGNN: Encrypted Traffic Classification based on Weaved Flow Fragment via Ensemble Graph Neural Networks[J]. IEEE Transactions on Machine Learning in Communications and Networking, 2023. Link
• Xiao D, Zhang J A, Liu X, et al. A Two-Stage GCN-Based Deep Reinforcement Learning Framework for SFC Embedding in Multi-Datacenter Networks[J]. IEEE Transactions on Network and Service Management, 2023. Link
• Zhang P, Luo Z, Kumar N, et al. CE-VNE: Constraint escalation virtual network embedding algorithm assisted by graph convolutional networks[J]. Journal of Network and Computer Applications, 2023: 103736. Link
• Chen Z, Zhu B, Zhou C. Container cluster placement in edge computing based on reinforcement learning incorporating graph convolutional networks scheme[J]. Digital Communications and Networks, 2023. Link
• Yao Z, Xia S, Li Y, et al. Cooperative Task Offloading and Service Caching for Digital Twin Edge Networks: A Graph Attention Multi-Agent Reinforcement Learning Approach[J]. IEEE Journal on Selected Areas in Communications, 2023. Link
• Helm M, Jaeger B, Carle G. Data-efficient GNN Models of Communication Networks using Beta-Distribution-based Sample Ranking[J]. ITU Journal on Future and Evolving Technologies, 2023, 4(3): 485–491. Link
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• Deng W, Liu Y, Li M, et al. GNN-Aided User Association and Beam Selection for mmWave Integrated Heterogeneous Networks[J]. IEEE Wireless Communications Letters, 2023. Link
• Guo H, Zhou Z, Zhao D, et al. EGNN: Energy-efficient anomaly detection for IoT multivariate time series data using graph neural network[J]. Future Generation Computer Systems, 2024, 151: 45-56. Link
• Zhang H, Ma X, Liu X, et al. GNN-based Power Allocation and User Association in Digital Twin Network for the Terahertz Band[J]. IEEE Journal on Selected Areas in Communications, 2023. Link
• Wei H, Zhao Y, Xu K. G-Routing: Graph Neural Networks-Based Flexible Online Routing[J]. IEEE Network, 2023, 37(4): 90-96. Link
• Wang G, Cheng P, Chen Z, et al. Inverse Reinforcement Learning with Graph Neural Networks for Full-Dimensional Task Offloading in Edge Computing[J]. IEEE Transactions on Mobile Computing, 2023. Link
• Xiao J, Yang L, Zhong F, et al. Robust Anomaly-based Insider Threat Detection using Graph Neural Network[J]. IEEE Transactions on Network and Service Management, 2023. Link
• Liao Y, Hashemi S A, Yang H, et al. Scalable Polar Code Construction for Successive Cancellation List Decoding: A Graph Neural Network-Based Approach[J]. IEEE Transactions on Communications, 2023. Link
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• Guo H, Zhou Z, Zhao D, et al. EGNN: Energy-efficient anomaly detection for IoT multivariate time series data using graph neural network[J]. Future Generation Computer Systems, 2024, 151: 45-56. Link
• Zhou X, Zhang J, Wen C K, et al. Graph Neural Network-Enhanced Expectation Propagation Algorithm for MIMO Turbo Receivers[J]. IEEE Transactions on Signal Processing, 2023, 71: 3458-3473. Link
• Zhang A, Zhang B, Bi W, et al. Multi-UAV task allocation based on GCN-inspired binary stochastic L-BFGS[J]. Computer Communications, 2023. Link
• He Y, Zhong X, Gan Y, et al. A DDPG Hybrid of Graph Attention Network and Action Branching for Multi-Scale End-Edge-Cloud Vehicular Orchestrated Task Offloading[J]. IEEE Wireless Communications, 2023. Link
• Wang X, Fu Z, Li X. A Graph Deep Learning-based Fault Detection and Positioning Method for Internet Communication Networks[J]. IEEE Access, 2023. Link
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• Ye Z, Wang K, Chen Y, et al. Multi-UAV navigation for partially observable communication coverage by graph reinforcement learning[J]. IEEE Transactions on Mobile Computing, 2023. Link
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