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GNN-Communication-Networks

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:

  • Jianping W, Guangqiu Q, Chunming W, et al. Federated learning for network attack detection using attention-based graph neural networks[J]. Scientific Reports, 2024, 14(1): 19088. Link
  • 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
  • Jiang W, Han H, Zhang Y, et al. Graph Neural Networks for Routing Optimization: Challenges and Opportunities[J]. Sustainability, 2024, 16(21): 9239. Link

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Other Surveys

  • He S, Xiong S, Ou Y, et al. An overview on the application of graph neural networks in wireless networks[J]. IEEE Open Journal of the Communications Society, 2021. Link
  • 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
  • Tam P, Song I, Kang S, et al. Graph Neural Networks for Intelligent Modelling in Network Management and Orchestration: A Survey on Communications[J]. Electronics, 2022, 11(20): 3371. Link
  • Ivanov A, Tonchev K, Poulkov V, et al. Graph-Based Resource Allocation for Integrated Space and Terrestrial Communications[J]. Sensors, 2022, 22(15): 5778. Link
  • Lee M, Yu G, Dai H, et al. Graph Neural Networks Meet Wireless Communications: Motivation, Applications, and Future Directions[J]. IEEE Wireless Communications, 2022, 29(5): 12-19. Link
  • 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

Competition

  • 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

Tool

  • 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

Literature

The list would be updated monthly.

2024

Journal

  • Wang Q, Wang X, Liu H, et al. A Domain Adaptive IoT Intrusion Detection Algorithm Based on GWR-GCN Feature Extraction and Conditional Domain Adversary[J]. IEEE Internet of Things Journal, 2024. Link
  • Xiaoyu Z, Peihan Q, Qi L, et al. A graph-based semi-supervised approach for few-shot class-incremental modulation classification[J]. China Communications, 2024. Link
  • Dai Y, Lyu L, Cheng N, et al. A Survey of Graph-Based Resource Management in Wireless Networks-Part I: Optimization Approaches[J]. IEEE Transactions on Cognitive Communications and Networking, 2024. Link
  • Dai Y, Lyu L, Cheng N, et al. A Survey of Graph-Based Resource Management in Wireless Networks-Part II: Learning Approaches[J]. IEEE Transactions on Cognitive Communications and Networking, 2024. Link
  • Dai B, Li H, Huang W. Distributed on-demand Routing Algorithm with Graph Representation Learning for Industrial IoT[J]. IEEE Transactions on Network Science and Engineering, 2024. Link
  • Sun H, Liao X, Wang J, et al. Fast and Scalable ACL Policy Solving Under Complex Constraints With Graph Neural Networks[J]. IEEE/ACM Transactions on Networking, 2024. Link
  • Chen D, Zhang W, Gao D, et al. GFlow: GNN-Based Optimal Flow Scheduling for Multipath Transmission with Link Overlapping[J]. IEEE Transactions on Network Science and Engineering, 2024. Link
  • Luo J, Fei Z, Wang X, et al. GNN Based Resource Allocation for Digital Twin-Enhanced Multi-UAV Radar Networks[J]. IEEE Wireless Communications Letters, 2024. Link
  • Wu H, Tian L, Tang H, et al. Graph Convolutional Reinforcement Learning-Guided Joint Trajectory Optimization and Task Offloading for Aerial Edge Computing[J]. IEEE Transactions on Intelligent Transportation Systems, 2024. Link
  • Jiang W, Han H, Zhang Y, et al. Graph Neural Networks for Routing Optimization: Challenges and Opportunities[J]. Sustainability, 2024, 16(21): 9239. Link
  • Huang Z, Yu F R, Cai J. Knowledge Collaboration-Based Resource Allocation in 6G IoT: A Graph Attention RL Approach[J]. IEEE Internet of Things Journal, 2024. Link
  • Jie Y, Jingchao H, Nan C, et al. Multilayer satellite network collaborative mobile edge caching: A GCN-based multi-agent approach[J]. China Communications, 2024, 21(11): 56-74. Link
  • Xu A, Hu Z, Li X, et al. TransEdge: Task Offloading with GNN and DRL in Edge Computing-Enabled Transportation Systems[J]. IEEE Internet of Things Journal, 2024. Link
  • Hu H, Xie Z, Shi H, et al. Unsupervised Power Allocation Based on Combination of Edge Aggregated Graph Attention Network with Deep Unfolded WMMSE[J]. IEEE Transactions on Vehicular Technology, 2024. Link Code
  • Shen J, Lin Y, Zhang Y, et al. Content Caching-Assisted Vehicular Edge Computing Using Multi-Agent Graph Attention Reinforcement Learning[J]. IEEE Transactions on Vehicular Technology, 2024. Link
  • Kim J, Cho Y, Kim J. Edge Convolution Graph Neural Network assisted Power Allocation for Wireless IoT Networks[J]. IEEE Access, 2024. Link
  • Pan Y, Wang X, Xu Z, et al. GNN-Empowered Effective Partial Observation MARL Method for AoI Management in Multi-UAV Network[J]. IEEE Internet of Things Journal, 2024. Link Code
  • Wang S, Zhang S, Ma J, et al. Graph Neural Network-Based WiFi Indoor Localization System With Access Point Selection[J]. IEEE Internet of Things Journal, 2024. Link
  • Zhang S, Liu A, Han C, et al. GRLR: Routing With Graph Neural Network and Reinforcement Learning for Mega LEO Satellite Constellations[J]. IEEE Transactions on Vehicular Technology, 2024. Link
  • Li X, Zhang S, Li H, et al. RadioGAT: A Joint Model-based and Data-driven Framework for Multi-band Radiomap Reconstruction via Graph Attention Networks[J]. IEEE Transactions on Wireless Communications, 2024. Link
  • Wan S, Wang Z, Zhou Y. Scalable Hybrid Beamforming for Multi-User MISO Systems: A Graph Neural Network Approach[J]. IEEE Transactions on Wireless Communications, 2024. Link
  • Mehrabian A, Wong V W S. Joint Spectrum, Precoding, and Phase Shifts Design for RIS-Aided Multiuser MIMO THz Systems[J]. IEEE Transactions on Communications, 2024. Link Code
  • Ma H, Gu Y, Wu H, et al. A dual incentive mechanism based on graph attention neural network and contract in mobile opportunistic networks[J]. Physical Communication, 2024, 67: 102485. Link
  • Wang X, Guan K, He D, et al. Graph Neural Network enabled Propagation Graph Method for Channel Modeling[J]. IEEE Transactions on Vehicular Technology, 2024. Link
  • Jiang Q, Xu X, Bilal M, et al. Potential game based distributed IoV service offloading with graph attention networks in mobile edge computing[J]. IEEE Transactions on Intelligent Transportation Systems, 2024. Link
  • Yonghui H, Zuodong J, Peng Q, et al. Task offloading and resource allocation in NOMA-VEC: A multi-agent deep graph reinforcement learning algorithm[J]. China Communications, 2024, 21(8): 79-88. Link
  • Geng Z, She C, Wang R, et al. Zero-Shot Learning for Beam Management in LEO Satellite Communications[J]. IEEE Transactions on Wireless Communications, 2024. Link
  • Esmaeili B, Azmoodeh A, Dehghantanha A, et al. A GNN-Based adversarial internet of things Malware Detection Framework for critical infrastructure: Studying Gafgyt, Mirai and Tsunami campaigns[J]. IEEE Internet of Things Journal, 2024. Link Code
  • Li F, Lin J, Wang Y, et al. Distributed Hierarchical Temporal Graph Learning for Communication-Efficient High-Dimensional Industrial IoT Modeling[J]. IEEE Internet of Things Journal, 2024. Link
  • Tran D H, Park M. FN-GNN: A Novel Graph Embedding Approach for Enhancing Graph Neural Networks in Network Intrusion Detection Systems[J]. Applied Sciences, 2024, 14(16): 6932. Link
  • Ahmadi M, Moayyedi A, Sulaiman M, et al. Generalizable 5G RAN/MEC Slicing and Admission Control for Reliable Network Operation[J]. IEEE Transactions on Network and Service Management, 2024. Link
  • Li Y, Lu Y, Ai B, et al. GNN-based beamforming for sum-rate maximization in MU-MISO networks[J]. IEEE Transactions on Wireless Communications, 2024. Link
  • Wang Z, Bennis M, Zhou Y. Graph Attention-based MADRL for Access Control and Resource Allocation in Wireless Networked Control Systems[J]. IEEE Transactions on Wireless Communications, 2024. Link
  • Gu Y, She C, Bi S, et al. Graph Neural Network for Distributed Beamforming and Power Control in Massive URLLC Networks[J]. IEEE Transactions on Wireless Communications, 2024. Link Code
  • Kumar G R S, Arul Geetha G. Graph neural networks based queuing model for optimal load balancing in mobile ad hoc network[J]. International Journal of Communication Systems, e5922, 2024. Link
  • Wu Y, Liu J, Wang C, et al. Graph Transformer and LSTM Attention for VNF Multi-Step Workload Prediction in SFC[J]. IEEE Transactions on Network and Service Management, 2024. Link
  • Feng Z, Wu D, Huang M, et al. Graph Attention-Based Reinforcement Learning for Trajectory Design and Resource Assignment in Multi-UAV Assisted Communication[J]. IEEE Internet of Things Journal, 2024. Link
  • Yang M, Zhai D, Zhang R, et al. Joint Admission and Power Control for Massive Connections via Graph Neural Network[J]. IEEE Transactions on Vehicular Technology, 2024. Link
  • Liu J, Xu Z, Wang C, et al. Mobility-Aware MEC Planning With a GNN-Based Graph Partitioning Framework[J]. IEEE Transactions on Network and Service Management, 2024. Link
  • Yang Y, Feng L, Sun Y, et al. Multi-cluster Cooperative Offloading for VR Task: A MARL Approach with Graph Embedding[J]. IEEE Transactions on Mobile Computing, 2024. Link
  • Zhang P, Li Y, Vasilakos A V, et al. Optimizing network resource allocation with graph pointer neural network in large-scale AI systems[J]. Digital Communications and Networks, 2024. Link
  • Wang C, Peng J, Cai L, et al. Proactive Bandwidth Allocation for V2X Networks with Multi-attentional Deep Graph Learning[J]. IEEE Transactions on Wireless Communications, 2024. Link
  • Jiang Z, Li J, Hu Q, et al. Scalable Graph-Aware Edge Representation Learning for Wireless IoT Intrusion Detection[J]. IEEE Internet of Things Journal, 2024. Link
  • Guo J, Yang C. A Model-based GNN for Learning Precoding[J]. IEEE Transactions on Wireless Communications, 2024. Link
  • Zhuang W, Mao Y, He H, et al. Approximate Message Passing-Enhanced Graph Neural Network for OTFS Data Detection[J]. IEEE Wireless Communications Letters, 2024. Link
  • Wang Y, Wu H, Li R. Deep Graph Reinforcement Learning for Mobile Edge Computing: Challenges and Solutions[J]. IEEE Network, 2024. Link Code
  • Li F, Yang J, Lam K Y, et al. Dynamic spectrum access for Internet-of-Things with joint GNN and DQN[J]. Ad Hoc Networks, 2024: 103596. Link
  • Chen B J, Chang R Y, Chien F T, et al. Energy-Efficient Multi-RIS-Aided Rate-Splitting Multiple Access: A Graph Neural Network Approach[J]. IEEE Wireless Communications Letters, 2024. Link
  • Zhang J, Miao C W, Huang J Q, et al. Fractional function energy efficiency optimization in wireless networks: A graph convolutional network approach[J]. Ad Hoc Networks, 2024, 160: 103509. Link
  • Wang S, Cao H, Yang L, et al. GCN-Based Multi-Agent Deep Reinforcement Learning for Dynamic Service Function Chain Deployment in IoT[J]. IEEE Transactions on Consumer Electronics, 2024. Link
  • Sun W, Zou Y, Guan N, et al. Graph Attention Network–Based Deep Reinforcement Learning Scheduling Framework for in-Vehicle Time-Sensitive Networking[J]. IEEE Transactions on Industrial Informatics, 2024. Link
  • Marwani M, Kaddoum G. Graph Neural Networks Approach for Joint Wireless Power Control and Spectrum Allocation[J]. IEEE Transactions on Machine Learning in Communications and Networking, 2024. Link Code
  • Ding M, Guo Y, Huang Z, et al. GROM: A generalized routing optimization method with graph neural network and deep reinforcement learning[J]. Journal of Network and Computer Applications, 2024, 229: 103927. Link
  • Ros S, Tam P, Song I, et al. Handling Efficient VNF Placement with Graph-Based Reinforcement Learning for SFC Fault Tolerance[J]. Electronics, 2024, 13(13): 2552. Link
  • Li B, Perazzone J, Swami A, et al. Learning to Transmit with Provable Guarantees in Wireless Federated Learning[J]. IEEE Transactions on Wireless Communications, 2024. Link Code
  • Yang J, Jiang X, Lei Y, et al. MTSecurity: Privacy-Preserving Malicious Traffic Classification using Graph Neural Network and Transformer[J]. IEEE Transactions on Network and Service Management, 2024. Link
  • Wang T, Ouyang X, Sun D, et al. Offloading Strategy Based on Graph Neural Reinforcement Learning in Mobile Edge Computing[J]. Electronics, 2024, 13(12): 2387. Link
  • Jamshidiha S, Pourahmadi V, Mohammadi A, et al. Power allocation using spatio-temporal graph neural networks and reinforcement learning[J]. Wireless Networks, 2024: 1-14. Link
  • Daneshvar S M M H, Mazinani S M. Training a Graph Neural Network to solve URLLC and eMBB coexisting in 5G networks[J]. Computer Communications, 2024. Link
  • Wang T, Shen L, Fan Q, et al. Joint Admission Control and Resource Allocation of Virtual Network Embedding via Hierarchical Deep Reinforcement Learning[J]. IEEE Transactions on Services Computing, 2024. Link Code
  • Adeogun D A R, Berardinelli G. Power control for 6G in-factory subnetworks with partial channel information using graph neural networks[J]. IEEE Open Journal of the Communications Society, 2024. Link
  • Lin J, Lan T, Zhang B, et al. Multi-Scenario Cellular KPI Prediction Based on Spatiotemporal Graph Neural Network[J]. IEEE Transactions on Automation Science and Engineering, 2024. Link
  • Zhang C, Yin J, Deng S. Ensuring Fairness in Edge Networks: A GNN-Based Media Workload Migration Scheme With Fairness Guarantee[J]. IEEE Transactions on Services Computing, 2024. Link
  • Wang Y, Li Y, Shi Q, et al. Engnn: A general edge-update empowered gnn architecture for radio resource management in wireless networks[J]. IEEE Transactions on Wireless Communications, 2024. Link
  • Zhao X, Peng C, Ding H, et al. An integrated graph data privacy attack framework based on graph neural networks in IoT[J]. Concurrency and Computation: Practice and Experience, e8209, 2024. Link
  • Zhong M, Lin M, Zhang C, et al. A Survey on Graph Neural Networks for Intrusion Detection Systems: Methods, Trends and Challenges[J]. Computers & Security, 2024: 103821. Link
  • Pei X, Deng X, Tian S, et al. A Privacy-Preserving Graph Neural Network for Network Intrusion Detection[J]. IEEE Transactions on Dependable and Secure Computing, 2024. Link
  • Wu Z, Ding D, Xiu Y, et al. Robust QoS prediction based on reputation integrated graph convolution network[J]. IEEE Transactions on Services Computing, 2024. Link
  • Ghasemi A, Zeraatkar E, Moradikia M, et al. Adversarial Attacks on Graph Neural Networks based Spatial Resource Management in P2P Wireless Communications[J]. IEEE Transactions on Vehicular Technology, 2024. Link
  • Yang J, Xu J, Zhang Y, et al. Graph attention network-based precoding for reconfigurable intelligent surfaces aided wireless communication systems[J]. IEEE Transactions on Vehicular Technology, 2024. Link
  • Zhang X, Zhao H, Xiong J, et al. Decentralized Routing and Radio Resource Allocation in Wireless Ad Hoc Networks via Graph Reinforcement Learning[J]. IEEE Transactions on Cognitive Communications and Networking, 2024. Link Code
  • Li X, Chen M, Hu Y, et al. Jointly Optimizing Terahertz based Sensing and Communications in Vehicular Networks: A Dynamic Graph Neural Network Approach[J]. IEEE Transactions on Wireless Communications, 2024. Link
  • Cao Z, Deng X, Yue S, et al. Dependent Task Offloading in Edge Computing Using GNN and Deep Reinforcement Learning[J]. IEEE Internet of Things Journal, 2024. Link
  • Tan Y, Liu J, Wang J. 5G End-To-End Slice Embedding Based on Heterogeneous Graph Neural Network and Reinforcement Learning[J]. IEEE Transactions on Cognitive Communications and Networking, 2024. Link
  • 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
  • Park J, Choi B, Lee C, et al. Graph Neural Network-Based SLO-Aware Proactive Resource Autoscaling Framework for Microservices[J]. IEEE/ACM Transactions on Networking, 2024. Link
  • Wu Y, Nie L, Xiong X, et al. Incremental Update Intrusion Detection for Industry 5.0 Security: A Graph Attention Network-Enabled Approach[J]. IEEE Transactions on Consumer Electronics, 2024. Link
  • Yang H, Cheng N, Sun R, et al. Knowledge-Driven Resource Allocation for Wireless Networks: A WMMSE Unrolled Graph Neural Network Approach[J]. IEEE Internet of Things Journal, 2024. Link
  • Shi Y, Wang W, Zhu X, et al. Low Earth Orbit Satellite Network Routing Algorithm Based on Graph Neural Networks and Deep Q-Network[J]. Applied Sciences, 2024, 14(9): 3840. Link
  • Lian L, Chen N, Yuan X, et al. Low-complexity collaborative caching strategy based on spatio-temporal graph convolutional model[J]. Computer Networks, 2024: 110490. Link
  • 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
  • Alam S, Diaz Rivera J J, Sarwar M M S, et al. Assuring Efficient Path Selection in an Intent-Based Networking System: A Graph Neural Networks and Deep Reinforcement Learning Approach[J]. Journal of Network and Systems Management, 2024, 32(2): 41. Link
  • Narayanan S, Archana K S. Auto metric graph neural network optimized with woodpecker mating algorithm for detecting network layer attacks in mobile ad hoc networks[J]. Smart Science, 2024: 1-14. Link
  • Guo Z, Li F, Shen J, et al. ConfigReco: Network configuration recommendation with graph neural networks[J]. IEEE Network, 2024. Link
  • Han X, Xu G, Zhang M, et al. DE-GNN: Dual embedding with graph neural network for fine-grained encrypted traffic classification[J]. Computer Networks, 2024: 110372. Link
  • Yeh T J, Tsai W C, Chen C W, et al. Enhanced-GNN with Angular CSI for Beamforming Design in IRS-Assisted mmWave Communication Systems[J]. IEEE Communications Letters, 2024. Link
  • 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
  • Luu V C, Hong J P. GNN-Based Meta-Learning Approach for Adaptive Power Control in Dynamic D2D Communications[J]. IEEE Transactions on Vehicular Technology, 2024. Link
  • 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
  • Dhamala B K, Dawadi B R, Manzoni P, et al. Performance Evaluation of Graph Neural Network-Based RouteNet Model with Attention Mechanism[J]. Future Internet, 2024, 16(4): 116. Link
  • 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
  • Sun Q, He Y, Petrosian O. Resource allocation in heterogeneous network with node and edge enhanced graph attention network[J]. Applied Intelligence, 2024: 1-13. Link
  • 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
  • Chen H, Chen P, Wang B, et al. Graph neural network based robust anomaly detection at service level in SDN driven microservice system[J]. Computer Networks, 2024, 239: 110135. Link
  • 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

Conference

  • Loevenich J F, Lopes R R F. DRL meets GNN to improve QoS in Tactical MANETs[C]//NOMS 2024-2024 IEEE Network Operations and Management Symposium. IEEE, 2024: 1-4. Link
  • Vo V V, Raza S M, Le D T, et al. Graph Neural Networks for IoT Data Aggregation Scheduling[C]//NOMS 2024-2024 IEEE Network Operations and Management Symposium. IEEE, 2024: 1-7. Link
  • Li L, Kim K. GTT-NTP: A Graph Convolutional Networks-Based Network Traffic Prediction model[C]//NOMS 2024-2024 IEEE Network Operations and Management Symposium. IEEE, 2024: 1-7. Link
  • Hekmati A, Krishnamachari B. Graph Convolutional Networks for DDoS Attack Detection in a Lossy Network[C]//2024 IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN). IEEE, 2024: 158-163. Link Code
  • Wang T, Fan Q, Wang C, et al. FlagVNE: A Flexible and Generalizable Reinforcement Learning Framework for Network Resource Allocation[C]//International Joint Conference on Artificial Intelligence (IJCAI), 2024. Link Code
  • Jiao Y, Ho P H, Lu X, et al. On Board-Level Failure Localization in Optical Transport Networks Using Graph Neural Network[C]//2024 20th International Conference on the Design of Reliable Communication Networks (DRCN). IEEE, 2024: 54-61. Link
  • Das S, NaderiAlizadeh N, Ribeiro A. State-Augmented Information Routing In Communication Systems With Graph Neural Networks[C]//ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2024: 9181-9185. Link
  • Tao T, Hou J, Nayak A. A GNN-DRL-based Collaborative Edge Computing Strategy for Partial Offloading[C]//GLOBECOM 2023-2023 IEEE Global Communications Conference. IEEE, 2023: 3717-3722. Link
  • 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
  • Zhang L, Cheng H, Peng S, et al. Flowlet-Level Routing Optimization with GNN-Based Multi-Agent Deep Reinforcement Learning[C]//GLOBECOM 2023-2023 IEEE Global Communications Conference. IEEE, 2023: 5214-5219. Link
  • Langari A S, Yeganeh L, Nguyen K K. Grothendieck Graph Neural Network (GGNN): A Path-Based Framework For Network Modelling[C]//GLOBECOM 2023-2023 IEEE Global Communications Conference. IEEE, 2023: 6548-6553. Link
  • Shan L, Hu Y, Shan W, et al. MAGLN: Multi-Attention Graph Learning Network for Channel Estimation in Multi-User SIMO[C]//2023 28th Asia Pacific Conference on Communications (APCC). IEEE, 2023: 1-6. Link

Preprint

  • Hu S, Zou G, Yang S, et al. GACL: Graph Attention Collaborative Learning for Temporal QoS Prediction[J]. arXiv preprint arXiv:2408.10555, 2024. Link
  • Piroti S, Chawla A, Zanouda T. Mobile Network Configuration Recommendation using Deep Generative Graph Neural Network[J]. arXiv preprint arXiv:2406.04779, 2024. Link
  • Sun M, Li Z, Wu S, et al. A Homogeneous Graph Neural Network for Precoding and Power Allocation in Scalable Wireless Networks[J]. arXiv preprint arXiv:2408.17252, 2024. Link
  • Li B, Verma G, Efimov T, et al. GLANCE: Graph-based Learnable Digital Twin for Communication Networks[J]. arXiv preprint arXiv:2408.09040, 2024. Link
  • Wang Q, Lu Y, Chen W, et al. GNN-Enabled Optimization of Placement and Transmission Design for UAV Communications[J]. arXiv preprint arXiv:2410.02277, 2024. Link
  • Shan Z, Yi X, Liang L, et al. GRLinQ: An Intelligent Spectrum Sharing Mechanism for Device-to-Device Communications with Graph Reinforcement Learning[J]. arXiv preprint arXiv:2408.09394, 2024. Link
  • Huang K, Liang L, Yi X, et al. Meta-Learning Empowered Graph Neural Networks for Radio Resource Management[J]. arXiv preprint arXiv:2408.16239, 2024. Link
  • Zhang R, Lu Y, Chen W, et al. Model-Based GNN Enabled Energy-Efficient Beamforming for Ultra-Dense Wireless Networks[J]. arXiv preprint arXiv:2410.02289, 2024. Link
  • Wu Z, Ishigaki G, Gour R, et al. Multi-domain Network Slice Partitioning: A Graph Neural Network Algorithm[J]. arXiv preprint arXiv:2408.15342, 2024. Link
  • Hu Z, Han C, Gerstacker W, et al. Tera-SpaceCom: GNN-based Deep Reinforcement Learning for Joint Resource Allocation and Task Offloading in TeraHertz Band Space Networks[J]. arXiv preprint arXiv:2409.07911, 2024. Link
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  • Ji M, Wu Q, Fan P, et al. Graph Neural Networks and Deep Reinforcement Learning Based Resource Allocation for V2X Communications[J]. arXiv preprint arXiv:2407.06518, 2024. Link Code
  • Hou Y, Ye H, Zhang Y, et al. RoutePlacer: An End-to-End Routability-Aware Placer with Graph Neural Network[J]. arXiv preprint arXiv:2406.02651, 2024. Link Code
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  • Zheng C, Cai K. GeNet: A Graph Neural Network-based Anti-noise Task-Oriented Semantic Communication Paradigm[J]. arXiv preprint arXiv:2403.18296, 2024. Link Code
  • 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
  • Zacharopoulos K, Koutroumpas G, Arapakis I, et al. LightningNet: Distributed Graph-based Cellular Network Performance Forecasting for the Edge[J]. arXiv preprint arXiv:2403.18810, 2024. Link
  • Shokrnezhad M, Taleb T. ORIENT: A Priority-Aware Energy-Efficient Approach for Latency-Sensitive Applications in 6G[J]. arXiv preprint arXiv:2402.06931, 2024. Link
  • Weil J, Bao Z, Abboud O, et al. Towards Generalizability of Multi-Agent Reinforcement Learning in Graphs with Recurrent Message Passing[J]. arXiv preprint arXiv:2402.05027, 2024. Link Code
  • 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

2023

Journal

  • 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
  • Yu P, Zhang J, Fang H, et al. Digital Twin Driven Service Self-Healing with Graph Neural Networks in 6G Edge Networks[J]. IEEE Journal on Selected Areas in Communications, 2023. Link
  • Abdel-Basset M, Hawash H, Sallam K M, et al. Digital Twin for Optimization of Slicing-enabled Communication Networks: A Federated Graph Learning Approach[J]. IEEE Communications Magazine, 2023. Link
  • Alablani I, Alenazi M J F. DQN-GNN-Based User Association Approach for Wireless Networks[J]. Mathematics, 2023, 11(20): 4286. Link
  • Zhu R, Zhang W, Wang P, et al. Energy-Efficient Graph Reinforced vNFC Deployment in Elastic Optical Inter-DC Networks[J]. IEEE Transactions on Network Science and Engineering, 2023. Link
  • 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
  • Dhadhania A, Bhatia J, Mehta R, et al. Unleashing the power of SDN and GNN for network anomaly detection: State‐of‐the‐art, challenges, and future directions[J]. Security and Privacy, 2023, e337. Link
  • Hu Y, Min G, Li J, et al. VNF Migration in Digital Twin Network for NFV Environment[J]. Electronics, 2023, 12(20): 4324. Link
  • Li K, Zhou H, Tu Z, et al. AT-GCN: A DDoS attack path tracing system based on attack traceability knowledge base and GCN[J]. Computer Networks, 2023, 236: 110036. 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
  • 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
  • Wang Z, Zhou Y, Zou Y, et al. A graph neural network learning approach to optimize ris-assisted federated learning[J]. IEEE Transactions on Wireless Communications, 2023. Link Code
  • Wang S, Lei Y, Yang B, et al. A graph neural network-based data cleaning method to prevent intelligent fault diagnosis from data contamination[J]. Engineering Applications of Artificial Intelligence, 2023, 126: 107071. Link
  • Xu J, Wang Y, Zhang B, et al. A Graph reinforcement learning based SDN routing path selection for optimizing long-term revenue[J]. Future Generation Computer Systems, 2023. Link
  • THEIN T T, SHIRAISHI Y, MORII M. Few-Shot Learning-Based Malicious IoT Traffic Detection with Prototypical Graph Neural Networks[J]. IEICE TRANSACTIONS on Information and Systems, 2023, 106(9): 1480-1489. Link
  • Ghasemzadeh P, Hempel M, Wang H, et al. GGCNN: An efficiency-maximizing gated graph convolutional neural network architecture for automatic modulation identification[J]. IEEE Transactions On Wireless Communications, 2023. Link
  • Duan Y, Li C, Bai G, et al. MFGAD-INT: in-band network telemetry data-driven anomaly detection using multi-feature fusion graph deep learning[J]. Journal of Cloud Computing, 2023, 12(1): 1-16. Link
  • Ferriol-Galmés M, Paillisse J, Suárez-Varela J, et al. RouteNet-Fermi: Network Modeling With Graph Neural Networks[J]. IEEE/ACM Transactions on Networking, 2023. Link
  • da Silva E S A, Pedrini H, Santos A. Applying Graph Neural Networks to Support Decision Making on Collective Intelligent Transportation Systems[J]. IEEE Transactions on Network and Service Management, 2023. Link
  • Han X. Combining Graph Neural Network with Deep Reinforcement Learning for Resource Allocation in Computing Force Networks[J]. Frontiers of Information Technology & Electronic Engineering, 2023. Link
  • Zhang X, Zhang S, Xiao L, et al. Graph Neural Network Assisted Efficient Signal Detection for OTFS Systems[J]. IEEE Communications Letters, 2023. Link
  • Ma Z, Zhang S, Li N, et al. GraphNEI: A GNN-based network entity identification method for IP geolocation[J]. Computer Networks, 2023: 109946. Link Code
  • Zhang Y, Xiu S, Cai Y, et al. Scheduling of graph neural network and Markov based UAV mobile edge computing networks[J]. Physical Communication, 2023: 102160. Link
  • Asheralieva A, Niyato D. Secure and efficient coded multi-access edge computing with generalized graph neural networks[J]. IEEE Transactions on Mobile Computing, 2023. Link
  • Guo Y, Wang Y, Khan F, et al. Traffic Management in IoT Backbone Networks Using GNN and MAB with SDN Orchestration[J]. Sensors, 2023, 23(16): 7091. Link
  • 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. Link
  • 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. Link
  • 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. Link
  • 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. Link Code
  • 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. Link
  • 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. Link
  • 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. Link Code
  • 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. Link
  • 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. Link
  • 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. Link
  • Liu S, Onishi T, Taki M, et al. A Generalizable Indoor Propagation Model Based on Graph Neural Networks[J]. IEEE Transactions on Antennas and Propagation, 2023. Link
  • Altaf T, Wang X, Ni W, et al. A new concatenated Multigraph Neural Network for IoT intrusion detection[J]. Internet of Things, 2023: 100818. Link
  • Gao M, Wu L, Li Q, et al. Anomaly traffic detection in IoT security using graph neural networks[J]. Journal of Information Security and Applications, 2023, 76: 103532. Link
  • Wang Y, Zhang B, Ma J, et al. Artificial intelligence of things (AIoT) data acquisition based on graph neural networks: A systematical review[J]. Concurrency and Computation: Practice and Experience, e7827. Link
  • Hong Y, Li Q, Yang Y, et al. Graph based Encrypted Malicious Traffic Detection with Hybrid Analysis of Multi-view Features[J]. Information Sciences, 2023: 119229. 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
  • Xiao Y, Sun Z, Shi G, et al. Imitation Learning-based Implicit Semantic-aware Communication Networks: Multi-layer Representation and Collaborative Reasoning[J]. IEEE Journal on Selected Areas in Communications, 2023. Link Code
  • 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
  • Hu G, Xiao X, Shen M, et al. TCGNN: Packet-grained network traffic classification via Graph Neural Networks[J]. Engineering Applications of Artificial Intelligence, 2023, 123: 106531. Link
  • Chen G, Liu Y, Zhang T, et al. A Graph Neural Network based Radio Map Construction Method for Urban Environment[J]. IEEE Communications Letters, 2023. Link
  • Xu G, Xu M, Chen Y, et al. A Mobile Application-Classifying Method Based on a Graph Attention Network from Encrypted Network Traffic[J]. Electronics, 2023, 12(10): 2313. Link
  • Fu N, Cheng G, Su X. Accurate compressed traffic detection via traffic analysis using Graph Convolutional Network based on graph structure feature[J]. Computer Communications, 2023. Link
  • Zhang Y, Zhang M, Gui Y, et al. Adaptive graph convolutional recurrent neural networks for system-level mobile traffic forecasting[J]. China Communications, 2023. Link
  • Zhao H, Yang B, Cui J, et al. Effective Fault Scenario Identification for Communication Networks Via Knowledge-Enhanced Graph Neural Networks[J]. IEEE Transactions on Mobile Computing, 2023. Link
  • Asheralieva A, Niyato D, Miyanaga Y. Efficient Dynamic Distributed Resource Slicing in 6G Multi-Access Edge Computing Networks with Online ADMM and Message Passing Graph Neural Networks[J]. IEEE Transactions on Mobile Computing, 2023. Link
  • Ding S, Wang J, Fu X. GNN-Geo: A Graph Neural Network-based Fine-grained IP geolocation Framework[J]. IEEE Transactions on Network Science and Engineering, 2023. Link
  • Deng X, Sun J, Lu J. Graph Neural Network-Based Efficient Subgraph Embedding Method for Link Prediction in Mobile Edge Computing[J]. Sensors, 2023, 23(10): 4936. Link
  • Bilot T, El Madhoun N, Al Agha K, et al. Graph Neural Networks for Intrusion Detection: A Survey[J]. IEEE Access, 2023. Link
  • Lu P, Jing C, Zhu X. GraphSAGE-Based Multi-Path Reliable Routing Algorithm for Wireless Mesh Networks[J]. Processes, 2023, 11(4): 1255. Link
  • Yumlembam R, Issac B, Jacob S M, et al. Iot-based android malware detection using graph neural network with adversarial defense[J]. IEEE Internet of Things Journal, 2023. Link
  • Zhang Z, Tao M, Liu Y F. Learning to Beamform in Joint Multicast and Unicast Transmission with Imperfect CSI[J]. IEEE Transactions on Communications, 2023. Link
  • Li Z, Wang X, Pan L, et al. Network Topology Optimization via Deep Reinforcement Learning[J]. IEEE Transactions on Communications, 2023. Link
  • Yang S, Zhang L, Cui L, et al. RLCS: Towards a robust and efficient mobile edge computing resource scheduling and task offloading system based on graph neural network[J]. Computer Communications, 2023, 206: 38-50. Link
  • Li D, Zhang H, Ding H, et al. User Preference Learning-based Proactive Edge Caching for D2D-Assisted Wireless Networks[J]. IEEE Internet of Things Journal, 2023. Link Code
  • Shen Y, Zhang J, Song S H, et al. Graph neural networks for wireless communications: From theory to practice[J]. IEEE Transactions on Wireless Communications, 2023. Link Code
  • Mohsenivatani M, Ali S, Ranasinghe V, et al. Graph Representation Learning for Wireless Communications[J]. IEEE Communications Magazine, 2023. Link
  • Li Y, Lu Y, Zhang R, et al. Deep Learning for Energy Efficient Beamforming in MU-MISO Networks: A GAT-based Approach[J]. IEEE Wireless Communications Letters, 2023. Link Data
  • Ling C, Feng Z, Xu L, et al. An Edge Server Placement Algorithm Based on Graph Convolution Network[J]. IEEE Transactions on Vehicular Technology, 2023. Link
  • Zhu J, Li R, Ding G, et al. AoI-based Temporal Attention Graph Neural Network for Popularity Prediction and Content Caching[J]. IEEE Transactions on Cognitive Communications and Networking, 2023. Link
  • Wang D, Bai Y, Huang G, et al. Cache-Aided MEC for IoT: Resource Allocation Using Deep Graph Reinforcement Learning[J]. IEEE Internet of Things Journal, 2023. Link
  • Sivakumar N R, Nagarajan S M, Devarajan G G, et al. Enhancing network lifespan in wireless sensor networks using deep learning based Graph Neural Network[J]. Physical Communication, 2023: 102076. Link
  • Khalid Alkahtani H, Mahmood K, Khalid M, et al. Optimal Graph Convolutional Neural Network-Based Ransomware Detection for Cybersecurity in IoT Environment[J]. Applied Sciences, 2023, 13(8): 5167. Link
  • He Q, Wang Y, Wang X, et al. Routing Optimization With Deep Reinforcement Learning in Knowledge Defined Networking[J]. IEEE Transactions on Mobile Computing, 2023. Link
  • Wang Z, Hu J, Min G, et al. Spatial-Temporal Cellular Traffic Prediction for 5G and Beyond: A Graph Neural Networks-Based Approach[J]. IEEE Transactions on Industrial Informatics, 2023. Link
  • Hou J, Lu H, Nayak A. A GNN-based proactive caching strategy in NDN networks[J]. Peer-to-Peer Networking and Applications, 2023: 1-13. Link
  • Zhang X, Zhao H, Wei J, et al. Cooperative Trajectory Design of Multiple UAV Base Stations with Heterogeneous Graph Neural Networks[J]. IEEE Transactions on Wireless Communications, 2023. Link Code
  • Schynol L, Pesavento M. Coordinated sum-rate maximization in multicell MU-MIMO with deep unrolling[J]. IEEE Journal on Selected Areas in Communications, 2023. Link Code
  • Deng X, Zhu J, Pei X, et al. Flow Topology-based Graph Convolutional Network for Intrusion Detection in Label-Limited IoT Networks[J]. IEEE Transactions on Network and Service Management, 2023. Link
  • Fawaz H, Lesca J, Quang P T A, et al. Graph Convolutional Reinforcement Learning for Collaborative Queuing Agents[J]. IEEE Transactions on Network and Service Management, 2023. Link
  • Gu Y, She C, Quan Z, et al. Graph Neural Networks for Distributed Power Allocation in Wireless Networks: Aggregation Over-the-Air[J]. IEEE Transactions on Wireless Communications, 2023. Link Code
  • Wang Z, Li Z, Pan H, et al. Large-Scale Measurements and Prediction of DC-WAN Traffic[J]. IEEE Transactions on Parallel and Distributed Systems, 2023, 34(5): 1390-1405. Link Code
  • Liu W, Cai J, Zhu Y, et al. Load Balancing Inside Programmable Data Planes Based on Network Modeling Prediction Using a GNN with Network Behaviors[J]. Computer Networks, 2023: 109695. Link
  • Chen N, Shen S, Duan Y, et al. Non-Euclidean Graph-Convolution Virtual Network Embedding for Space–Air–Ground Integrated Networks[J]. Drones, 2023, 7(3): 165. Link
  • Gao H, Zhu Q, Wang W. Optimal deployment of large-scale wireless sensor networks based on graph clustering and matrix factorization[J]. EURASIP Journal on Advances in Signal Processing, 2023, 2023(1): 1-17. Link
  • Nerini M, Clerckx B. Overhead-Free Blockage Detection and Precoding Through Physics-Based Graph Neural Networks: LIDAR Data Meets Ray Tracing[J]. IEEE Wireless Communications Letters, 2023. Link
  • Pramod Kumar P, Sagar K. Reinforcement learning and neuro‐fuzzy GNN‐based vertical handover decision on internet of vehicles[J]. Concurrency and Computation: Practice and Experience, e7688, 2023. Link
  • Gao X, Wang J, Zhou M. The Research of Resource Allocation Method Based onGCN-LSTM in 5G NetworkK[J]. IEEE Communications Letters, 2023. Link
  • Lo W W, Kulatilleke G, Sarhan M, et al. XG-BoT: An explainable deep graph neural network for botnet detection and forensics[J]. Internet of Things, 2023: 100747. Link
  • Xu X, Liu Y, Chen Q, et al. Distributed Auto-Learning GNN for Multi-Cell Cluster-Free NOMA Communications[J]. IEEE Journal on Selected Areas in Communications, 2023. Link
  • Janu D, Kumar S, Singh K. A Graph Convolution Network Based Adaptive Cooperative Spectrum Sensing in Cognitive Radio Network[J]. IEEE Transactions on Vehicular Technology, 2023. Link
  • Wang Z, Zhou Y, Zou Y, et al. A Graph Neural Network Learning Approach to Optimize RIS-Assisted Federated Learning[J]. IEEE Transactions on Wireless Communications, 2023. Link Code
  • Diao Z, Xie G, Wang X, et al. EC-GCN: A encrypted traffic classification framework based on multi-scale graph convolution networks[J]. Computer Networks, 2023: 109614. Link
  • Zhou X, Bilal M, Dou R, et al. Edge Computation Offloading With Content Caching in 6G-Enabled IoV[J]. IEEE Transactions on Intelligent Transportation Systems, 2023. Link
  • Zhang H, Zeng K, Lin S. Federated Graph Neural Network for Fast Anomaly Detection in Controller Area Networks[J]. IEEE Transactions on Information Forensics and Security, 2023. Link
  • Ghasemzadeh P, Hempel M, Wang H, et al. GGCNN: An Efficiency-Maximizing Gated Graph Convolutional Neural Network Architecture for Automatic Modulation Identification[J]. IEEE Transactions on Wireless Communications, 2023. Link
  • Zeng L, Yang C, Huang P, et al. GNN at the Edge: Cost-Efficient Graph Neural Network Processing over Distributed Edge Servers[J]. IEEE Journal on Selected Areas in Communications, 2023. Link
  • Theodoropoulos T, Makris A, Kontopoulos I, et al. Graph neural networks for representing multivariate resource usage: A multiplayer mobile gaming case-study[J]. International Journal of Information Management Data Insights, 2023, 3(1): 100158. Link
  • Sun Z, Mo Y, Yu C. Graph Reinforcement Learning based Task offloading for Multi-access Edge Computing[J]. IEEE Internet of Things Journal, 2023. Link
  • Wei W, Fu L, Gu H, et al. GRL-PS: Graph embedding-based DRL approach for adaptive path selection[J]. IEEE Transactions on Network and Service Management, 2023. Link
  • Liu T, Li Z, Long H, et al. NT-GNN: Network Traffic Graph for 5G Mobile IoT Android Malware Detection[J]. Electronics, 2023, 12(4): 789. Link
  • Ren G, Cheng G, Fu N. Accurate Encrypted Malicious Traffic Identification via Traffic Interaction Pattern Using Graph Convolutional Network[J]. Applied Sciences, 2023, 13(3): 1483. Link

Conference

  • Wang X, Zhang Y. Network Attack Identification and Analysis Based on Graph Convolutional Neural Network[C]//2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). IEEE, 2023: 1443-1448. Link
  • Friji H, Mavromatis I, Sanchez-Mompo A, et al. Multi-stage Attack Detection and Prediction Using Graph Neural Networks: An IoT Feasibility Study[C]//2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). IEEE, 2023: 620-627. Link
  • Hasegawa K, Yamashita K, Hidano S, et al. Membership Inference Attacks against GNN-based Hardware Trojan Detection[C]//2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). IEEE, 2023: 1222-1229. Link
  • Tian T, Gong Y, Jiang B, et al. Insider Threat Detection Based On Heterogeneous Graph Neural Network[C]//2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). IEEE, 2023: 628-635. Link
  • Bellaj B, Ouaddah A, Mezrioui A, et al. Gbtrust: Leveraging edge attention in graph neural networks for trust management in p2p networks[C]//2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). IEEE, 2023: 1272-1278. Link
  • Chen S, Lin D, Xie Z, et al. Temporal-Gated Graph Neural Network with Graph Sampling for Multi-step Attack Detection[C]//2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). IEEE, 2023: 1266-1271. Link
  • Gowtham V, Schreiner F, Corici M I, et al. Intent-based Networking for QoS-aware Cloud and Transport Network Management based on Graph Neural Networks[C]//2023 IEEE Future Networks World Forum (FNWF). IEEE, 2023: 1-7. Link
  • Zhang G, Song J, Hu Y, et al. Fine-grained Task Scheduling Based on Graph Neural Network and Federated Learning in Vehicle Edge Computing[C]//2023 IEEE 29th International Conference on Parallel and Distributed Systems (ICPADS). IEEE, 2023: 2467-2474. Link
  • Meng Q, Luo Z, Zheng X, et al. Hierarchical Collaborative Resource Scheduling in Industrial Internet of Things based on Graph Neural Networks and Deep Reinforcement Learning[C]//2023 IEEE 29th International Conference on Parallel and Distributed Systems (ICPADS). IEEE, 2023: 2647-2654. Link
  • Xu T, Tan X, Zhang Z, et al. MIMO Detection Based on Graph Neural Network with Belief Propagation[C]//2023 International Conference on Wireless Communications and Signal Processing (WCSP). IEEE, 2023: 1095-1100. Link
  • Lin S, Lee M, Chen Q, et al. OverGNN Assisted Power Allocation for Heterogeneous Ultra-Dense Networks[C]//2023 International Conference on Wireless Communications and Signal Processing (WCSP). IEEE, 2023: 152-157. Link
  • Graham J, Medico A, Dividino R, et al. Edge Clustering and Communication Efficiency with GNNs in Internet of Vehicles[C]//International Conference on Wireless Intelligent and Distributed Environment for Communication. Cham: Springer Nature Switzerland, 2023: 47-64. Link Code
  • Gharavian V, Khosrowshahli R, Mahmoud Q H, et al. Intrusion Detection for Wireless Sensor Network Using Graph Neural Networks[C]//2023 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2023: 807-813. Link
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Preprint

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2022

Journal

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  • Wang X, Fu L, Cheng N, et al. Joint Flying Relay Location and Routing Optimization for 6G UAV–IoT Networks: A Graph Neural Network-Based Approach[J]. Remote Sensing, 2022, 14(17): 4377. Link
  • Zhang X, Zhang Z, Yang L. Learning-Based Resource Allocation in Heterogeneous Ultra Dense Network[J]. IEEE Internet of Things Journal, 2022. Link
  • Liu Z, Qiu H, Guo W, et al. NIE-GAT: Node Importance Evaluation Method for Inter-Domain Routing Network Based on Graph Attention Network[J]. Journal of Computational Science, 2022: 101885. Link
  • Zhang X. Path Selection Strategy of Communication Network Based on Graph Convolutional Neural Network[J]. Security and Communication Networks, 2022, 2022. Link
  • Zheng X, Huang W, Li H, et al. Research on Generalized Intelligent Routing Technology Based on Graph Neural Network[J]. Electronics, 2022, 11(18): 2952. Link
  • Peng Y, Liu C, Liu S, et al. SmartTRO: Optimizing topology robustness for Internet of Things via deep reinforcement learning with graph convolutional networks[J]. Computer Networks, 2022: 109385. Link
  • Chen N, Zhang P, Kumar N, et al. Spectral graph theory-based virtual network embedding for vehicular fog computing: A deep reinforcement learning architecture[J]. Knowledge-Based Systems, 2022, 257: 109931. Link
  • Guo J, Yang C. Learning power allocation for multi-cell-multi-user systems with heterogeneous graph neural networks[J]. IEEE Transactions on Wireless Communications, 2022, 21(2): 884-897. Link
  • Wang Z, Eisen M, Ribeiro A. Learning decentralized wireless resource allocations with graph neural networks[J]. IEEE Transactions on Signal Processing, 2022, 70: 1850-1863. Link
  • Huang R, Guan W, Zhai G, et al. Deep Graph Reinforcement Learning Based Intelligent Traffic Routing Control for Software-Defined Wireless Sensor Networks[J]. Applied Sciences, 2022, 12(4): 1951. Link
  • Fang Y, Ergüt S, Patras P. SDGNet: A Handover-Aware Spatiotemporal Graph Neural Network for Mobile Traffic Forecasting[J]. IEEE Communications Letters, 2022, 26(3): 582-586. Link
  • Li P, Wang L, Wu W, et al. Graph Neural Network-Based Scheduling for Multi-UAV-Enabled Communications in D2D Networks[J]. Digital Communications and Networks, 2022. Link
  • Govindaraju S, Vinisha W V R, Shajin F H, et al. Intrusion detection framework using auto‐metric graph neural network optimized with hybrid woodpecker mating and capuchin search optimization algorithm in IoT network[J]. Concurrency and Computation: Practice and Experience, e7197, 2022. Link
  • Zhou X, Liang W, Li W, et al. Hierarchical adversarial attacks against graph neural network based IoT network intrusion detection system[J]. IEEE Internet of Things Journal, 2022. Link
  • Cao H, Zhu W, Feng W, et al. Robust beamforming based on graph attention networks for IRS-assisted Satellite IoT Communications[J]. Entropy, 2022, 24(3): 326. Link
  • Peng S, Nie J, Shu X, et al. A multi-view framework for BGP anomaly detection via graph attention network[J]. Computer Networks, 2022, 214: 109129. Link
  • Yan B, Liu Q, Shen J L, et al. Flowlet-level multipath routing based on graph neural network in OpenFlow-based SDN[J]. Future Generation Computer Systems, 2022, 134: 140-153. Link
  • Almasan P, Xiao S, Cheng X, et al. ENERO: Efficient real-time WAN routing optimization with Deep Reinforcement Learning[J]. Computer Networks, 2022, 214: 109166. Link
  • Chen B, Zhu D, Wang Y, et al. An Approach to Combine the Power of Deep Reinforcement Learning with a Graph Neural Network for Routing Optimization[J]. Electronics, 2022, 11(3): 368. Link
  • Ma S, Yao H, Mai T, et al. Graph Convolutional Network Aided Virtual Network Embedding for Internet of Thing[J]. IEEE Transactions on Network Science and Engineering, 2022. Link
  • Ferriol-Galmés M, Suárez-Varela J, Paillissé J, et al. Building a digital twin for network optimization using graph neural networks[J]. Computer Networks, 2022: 109329. Link Code
  • Li Y, Li J, Pang J. A Graph Attention Mechanism-Based Multiagent Reinforcement-Learning Method for Task Scheduling in Edge Computing[J]. Electronics, 2022, 11(9): 1357. Link
  • He M, Zhuang L, Yang S, et al. An Energy-Efficient VNE Algorithm Based on Bidirectional Long Short-Term Memory[J]. Journal of Network and Systems Management, 2022, 30(3): 1-29. Link
  • Wang T, Chen S, Zhu Y, et al. LinkSlice: Fine-grained Network Slice Enforcement Based on Deep Reinforcement Learning[J]. IEEE Journal on Selected Areas in Communications, 2022. Link
  • Zhang Z, Jiang T, Yu W. Learning Based User Scheduling in Reconfigurable Intelligent Surface Assisted Multiuser Downlink[J]. IEEE Journal of Selected Topics in Signal Processing, 2022. Link
  • Wei L, Luo H X, Zhai S L, et al. GCN based virtual resource allocation scheme for power internet of things[J]. Journal of Computational Methods in Sciences and Engineering, 2022 (Preprint): 1-14. Link
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Conference

  • Xu H, Li S, Cheng Z, et al. VT-GAT: A Novel VPN Encrypted Traffic Classification Model Based on Graph Attention Neural Network[C]//International Conference on Collaborative Computing: Networking, Applications and Worksharing. Cham: Springer Nature Switzerland, 2022: 437-456. Link
  • He H, Su L, Ye K. GraphGRU: A Graph Neural Network Model for Resource Prediction in Microservice Cluster[C]//2022 IEEE 28th International Conference on Parallel and Distributed Systems (ICPADS). IEEE, 2023: 499-506. Link Code
  • Cheng P, Chen G, Han Z. Graph Neural Networks based Resource Allocation in Heterogeneous Wireless Networks[C]//Proceedings of the 7th International Conference on Intelligent Information Processing. 2022: 1-6. Link
  • Zhang J, Jiang Y, Liu X, et al. Design of Retransmission Mechanism for Decentralized Inference with Graph Neural Networks[C]//2022 27th Asia Pacific Conference on Communications (APCC). IEEE, 2022: 515-519. Link
  • Chen L, Yan N, Zhang B, et al. A General Backdoor Attack to Graph Neural Networks Based on Explanation Method[C]//2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). IEEE, 2022: 759-768. Link
  • Boukhtouta A, Madi T, Pourzandi M, et al. Cloud Native Applications Profiling using a Graph Neural Networks Approach[C]//2022 IEEE Future Networks World Forum (FNWF). IEEE, 2022: 220-227. Link
  • Yan N, Wen Y, Chen L, et al. Deepro: Provenance-based APT Campaigns Detection via GNN[C]//2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). IEEE, 2022: 747-758. Link
  • Liu Y, She C, Hardjawana W, et al. Graph Neural Networks for Timely Updates of Short Packets in Interference-Limited Networks[C]//2022 56th Asilomar Conference on Signals, Systems, and Computers. IEEE, 2022: 1050-1054. Link
  • Coleman J, Kiamari M, Clark L, et al. Graph Convolutional Network-based Scheduler for Distributing Computation in the Internet of Robotic Things[C]//MILCOM 2022-2022 IEEE Military Communications Conference (MILCOM). IEEE, 2022: 1070-1075. Link Code
  • Li B, Swami A, Segarra S. Power allocation for wireless federated learning using graph neural networks[C]//ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2022: 5243-5247. Link Code
  • Wang H, Zhang R, Cheng X, et al. Federated Spatio-Temporal Traffic Flow Prediction Based on Graph Convolutional Network[C]//2022 14th International Conference on Wireless Communications and Signal Processing (WCSP). IEEE, 2022: 221-225. Link
  • Tonchev K, Neshov N, Ivanov A, et al. Automatic Modulation Classification using Graph Convolutional Neural Networks for Time-frequency Representation[C]//2022 25th International Symposium on Wireless Personal Multimedia Communications (WPMC). IEEE, 2022: 75-79. Link
  • Bai Y, Wang D, Song B. A Knowledge Graph-based Cooperative Caching Scheme in MEC-enabled Heterogeneous Networks[C]//GLOBECOM 2022-2022 IEEE Global Communications Conference. IEEE, 2022: 5959-5964. Link
  • Kim J, Lee H, Park S H. Autoencoding Graph Neural Networks for Scalable Transceiver Design[C]//2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall). IEEE, 2022: 1-2. Link
  • Su Y, Zhou H, Deng Y. D2D-Based Cellular-Connected UAV Swarm Control Optimization via Graph-Aware DRL[C]//GLOBECOM 2022-2022 IEEE Global Communications Conference. IEEE, 2022: 1326-1331. Link
  • Randall M, Belzarena P, Larroca F, et al. Deep Reinforcement Learning and Graph Neural Networks for Efficient Resource Allocation in 5G Networks[C]//2022 IEEE Latin-American Conference on Communications (LATINCOM). IEEE, 2022: 1-6. Link Code
  • Lent R. Dynamic Routing in Challenged Networks with Graph Neural Networks[C]//2022 IEEE Latin-American Conference on Communications (LATINCOM). IEEE, 2022: 1-6. Link
  • Chen R, Shi H, Wu J, et al. GCNPart: Interference-Aware Resource Partitioning Framework with Graph Convolutional Neural Networks and Deep Reinforcement Learning[C]//Algorithms and Architectures for Parallel Processing: 22nd International Conference, ICA3PP 2022, Copenhagen, Denmark, October 10–12, 2022, Proceedings. Cham: Springer Nature Switzerland, 2023: 568-589. Link
  • Li N, Iosifidis A, Zhang Q. Graph Reinforcement Learning-based CNN Inference Offloading in Dynamic Edge Computing[C]//GLOBECOM 2022-2022 IEEE Global Communications Conference. IEEE, 2022: 982-987. Link
  • Zhu H, Lu J. Graph-based Intrusion Detection System Using General Behavior Learning[C]//GLOBECOM 2022-2022 IEEE Global Communications Conference. IEEE, 2022: 2621-2626. Link
  • Li C, Li F, Yu M, et al. Insider Threat Detection Using Generative Adversarial Graph Attention Networks[C]//GLOBECOM 2022-2022 IEEE Global Communications Conference. IEEE, 2022: 2680-2685. Link
  • Tonchev K, Ivanov A, Neshov N, et al. Learning Graph Convolutional Neural Networks to Predict Radio Environment Maps[C]//2022 25th International Symposium on Wireless Personal Multimedia Communications (WPMC). IEEE, 2022: 392-395. Link
  • Zhang H, Tian Q, Han Y. Multi channel spectrum prediction algorithm based on GCN and LSTM[C]//2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall). IEEE, 2022: 1-5. Link
  • Zhu R, Luo X, Yao J, et al. Prediction of Cellular Network Channel Utilization Based on Graph Convolutional Networks[C]//2022 IEEE 33rd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC). IEEE, 2022: 1233-1238. Link
  • He S, Ou Y, Wang L, et al. Representation Learning of Knowledge Graph for Wireless Communication Networks[C]//GLOBECOM 2022-2022 IEEE Global Communications Conference. IEEE, 2022: 1338-1343. Link
  • Li C, Lou J, Liu S, et al. Shapley Explainer-An Interpretation Method for GNNs Used in SDN[C]//GLOBECOM 2022-2022 IEEE Global Communications Conference. IEEE, 2022: 5534-5540. Link
  • Xu H, Li S, Cheng Z, et al. TrafficGCN: Mobile Application Encrypted Traffic Classification Based on GCN[C]//GLOBECOM 2022-2022 IEEE Global Communications Conference. IEEE, 2022: 891-896. Link
  • Geng Z, She C, Zhang D, et al. Zero-Shot Recurrent Graph Neural Networks for Beam Prediction in Non-Terrestrial Networks[C]//2022 IEEE Globecom Workshops (GC Wkshps). IEEE, 2022: 1400-1405. Link
  • Herath J D, Wakodikar P P, Yang P, et al. CFGExplainer: Explaining Graph Neural Network-Based Malware Classification from Control Flow Graphs[C]//2022 52nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). IEEE, 2022: 172-184. Link Code
  • Yaqoob M, Trestian R, Nguyen H X. Data-driven network performance prediction for B5G networks: a graph neural network approach[C]//2022 IEEE Ninth International Conference on Communications and Electronics (ICCE). IEEE, 2022: 55-60. Link
  • Hara T, Sasabe M. Deep Reinforcement Learning with Graph Neural Networks for Capacitated Shortest Path Tour based Service Chaining[C]//2022 18th International Conference on Network and Service Management (CNSM). IEEE, 2022: 19-27. Link
  • Bhavanasi S S, Pappone L, Esposito F. Routing with Graph Convolutional Networks and Multi-Agent Deep Reinforcement Learning[C]//2022 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN). IEEE, 2022: 72-77. Link
  • Zhou X, Zhang J, Wen C K, et al. Extrinsic Graph Neural Network-Aided Expectation Propagation for Turbo-MIMO Receiver[C]//2022 International Symposium on Wireless Communication Systems (ISWCS). IEEE, 2022: 1-6. Link
  • Li Y, Xie Q, Wang W, et al. GCN-Based Topology Design for Decentralized Federated Learning in IoV[C]//2022 23rd Asia-Pacific Network Operations and Management Symposium (APNOMS). IEEE, 2022: 1-6. Link
  • Yang L, Cheng M, Qu J, et al. GraphHO: A Graph-based Handover Optimization System for Cellular Networks[C]//2022 International Symposium on Wireless Communication Systems (ISWCS). IEEE, 2022: 1-6. Link
  • Sun X, Yang J. HetGLM: Lateral Movement Detection by Discovering Anomalous Links with Heterogeneous Graph Neural Network[C]//2022 IEEE International Performance, Computing, and Communications Conference (IPCCC). IEEE, 2022: 404-411. Link
  • Hou Q, Lee M, Yu G, et al. Learning to Optimize Resource in Dynamic Wireless Environment via Meta-Gating Graph Neural Network[C]//2022 International Symposium on Wireless Communication Systems (ISWCS). IEEE, 2022: 1-6. Link
  • Heo D N, Lee D, Kim H G, et al. Reinforcement Learning of Graph Neural Networks for Service Function Chaining in Computer Network Management[C]//2022 23rd Asia-Pacific Network Operations and Management Symposium (APNOMS). IEEE, 2022: 1-6. Link
  • Jin Y, Vannella F, Bouton M, et al. A Graph Attention Learning Approach to Antenna Tilt Optimization[C]//2022 1st International Conference on 6G Networking (6GNet). IEEE, 2022: 1-5. Link
  • Ghasemzadeh P, Hempel M, Sharif H. A Robust Graph Convolutional Neural Network-Based Classifier for Automatic Modulation Recognition[C]//2022 International Wireless Communications and Mobile Computing (IWCMC). IEEE, 2022: 907-912. Link
  • Wu J, Wang F, Yao H, et al. Autonomous Operation and Maintenance Technology of Optical Network Based on Graph Neural Network[C]//2022 International Wireless Communications and Mobile Computing (IWCMC). IEEE, 2022: 766-772. Link
  • Harris D, Raz D, Sagiv P. Bandwidth resource allocation in integrated access and backhaul networks[C]//Proceedings of the ACM SIGCOMM Workshop on 5G and Beyond Network Measurements, Modeling, and Use Cases. 2022: 1-7. Link
  • Hoarau K, Tournoux P U, Razafindralambo T. BGNN: Detection of BGP Anomalies Using Graph Neural Networks[C]//2022 IEEE Symposium on Computers and Communications (ISCC). IEEE, 2022: 1-6. Link Code
  • Schynol L, Pesavento M. Deep Unfolding in Multicell MU-MIMO[C]//2022 30th European Signal Processing Conference (EUSIPCO). IEEE, 2022: 1631-1635. Link Code
  • Mohammedi E H, Lavinal E, Fleury G. Detecting and locating configuration errors in IP VPNs with Graph Neural Networks[C]//NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium. IEEE, 2022: 1-6. Link
  • Rusek K, Almasan P, Suárez-Varela J, et al. Fast Traffic Engineering by Gradient Descent with Learned Differentiable Routing[C]. International Conference on Network and Service Management (CNSM), 2022. Link
  • Zhao R, Deng X, Wang Y, et al. Flow Sequence-Based Anonymity Network Traffic Identification with Residual Graph Convolutional Networks[C]//2022 IEEE/ACM 30th International Symposium on Quality of Service (IWQoS). IEEE, 2022: 1-10. Link
  • Hou J, Lu H, Nayak A. GNN-GM: A Proactive Caching Scheme for Named Data Networking[C]//2022 IEEE International Conference on Communications Workshops (ICC Workshops). IEEE, 2022: 1-6. Link
  • Yen C C, Sun W, Purmehdi H, et al. Graph Neural Network based Root Cause Analysis Using Multivariate Time-series KPIs for Wireless Networks[C]//NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium. IEEE, 2022: 1-7. Link
  • Li Y, Li R, Zhou Z, et al. GraphDDoS: Effective DDoS Attack Detection Using Graph Neural Networks[C]//2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design (CSCWD). IEEE, 2022: 1275-1280. Link
  • Houidi O, Bakri S, Zeghlache D. Multi-Agent Graph Convolutional Reinforcement Learning for Intelligent Load Balancing[C]//NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium. IEEE, 2022: 1-6. Link
  • Ji Y, Huang H H. NestedGNN: Detecting Malicious Network Activity with Nested Graph Neural Networks[C]//ICC 2022-IEEE International Conference on Communications. IEEE, 2022: 2694-2699. Link
  • Yu Q, Wang H, Li T, et al. Network Traffic Overload Prediction with Temporal Graph Attention Convolutional Networks[C]//2022 IEEE International Conference on Communications Workshops (ICC Workshops). IEEE, 2022: 885-890. Link
  • Jin Y, Daoutis M, Girdzijauskas S, et al. Open World Learning Graph Convolution for Latency Estimation in Routing Networks[C]//2022 International Joint Conference on Neural Networks (IJCNN). IEEE, 2022: 1-8. Link Code
  • Paudel R, Huang H H. Pikachu: Temporal Walk Based Dynamic Graph Embedding for Network Anomaly Detection[C]//NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium. IEEE, 2022: 1-7. Link
  • Oshio K, Takada S, Han C, et al. Poster: Flexible Function Estimation of IoT Malware Using Graph Embedding Technique[C]//2022 IEEE Symposium on Computers and Communications (ISCC). IEEE, 2022: 1-3. Link
  • Hui N, Sun Q, Wang Y, et al. Wireless Resource Allocation based on Multiplexing and Isolation in Sliced 5G Networks[C]//2022 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2022: 1629-1634. Link
  • NaderiAlizadeh N, Eisen M, Ribeiro A. Adaptive Wireless Power Allocation with Graph Neural Networks[C]//ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2022: 5213-5217. Link
  • Zhao Z, Verma G, Swami A, et al. Delay-Oriented Distributed Scheduling Using Graph Neural Networks[C]. ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2022: 8902-8906. Link Code
  • Lo W W, Layeghy S, Sarhan M, et al. E-GraphSAGE: A Graph Neural Network based Intrusion Detection System[C]. NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium. IEEE, 2022: 1-9. Link
  • Wang M, Hui L, Cui Y, et al. xNet: Improving Expressiveness and Granularity for Network Modeling with Graph Neural Networks[C]//IEEE INFOCOM 2022-IEEE Conference on Computer Communications. IEEE, 2022: 2028-2037. Link
  • Happ M, Du J L, Herlich M, et al. Exploring the Limitations of Current Graph Neural Networks for Network Modeling[C]. Proceedings of the IEEE/IFIP Network Operations and Management Symposium, 2022. Link
  • Güemes-Palau C, Almasan P, Xiao S, et al. Accelerating Deep Reinforcement Learning for Digital Twin Network Optimization with Evolutionary Strategies[C]//NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium. IEEE, 2022: 1-5. Link
  • Ferriol-Galmés M, Rusek K, Suárez-Varela J, et al. Routenet-erlang: A graph neural network for network performance evaluation[C]//IEEE INFOCOM 2022-IEEE Conference on Computer Communications. IEEE, 2022: 2018-2027. Link Code
  • Zhu J, Li R, Zhao Z, et al. AoI-based Temporal Attention Graph Neural Network for Popularity Prediction in ICN[C]//2022 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2022: 1284-1289. Link
  • Dai Z, Liu C H, Ye Y, et al. AoI-minimal UAV Crowdsensing by Model-based Graph Convolutional Reinforcement Learning[C]//IEEE INFOCOM 2022-IEEE Conference on Computer Communications. IEEE, 2022: 1029-1038. Link
  • Zhao Z, Swami A, Segarra S. Distributed Link Sparsification for Scalable Scheduling Using Graph Neural Networks[C]//ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2022: 5308-5312. Link
  • Zhu X, Zhang Y, Zhang Z, et al. Interpretability Evaluation of Botnet Detection Model based on Graph Neural Network[C]//IEEE INFOCOM 2022-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). IEEE, 2022: 1-6. Link
  • Farreras M, Soto P, Camelo M, et al. Predicting network performance using GNNs: generalization to larger unseen networks[C]//NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium. IEEE, 2022: 1-6. Link
  • Zhang Z, Jiang T, Yu W. User Scheduling Using Graph Neural Networks for Reconfigurable Intelligent Surface Assisted Multiuser Downlink Communications[C]//ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2022: 8892-8896. Link
  • Lian L, Chen N, Ou P, et al. Mobile Edge Cooperative Caching Strategy Based on Spatio-temporal Graph Convolutional Model[C]//2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design (CSCWD). IEEE, 2022: 1396-1401. Link
  • Ferriol-Galmés M, Cheng X, Shi X, et al. FlowDT: A Flow-Aware Digital Twin for Computer Networks[C]//ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2022: 8907-8911. Link
  • Kosasih A, Onasis V, Hardjawana W, et al. Graph Neural Network Aided Expectation Propagation Detector for MU-MIMO Systems[C]. 2022 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2022: 1212-1217. Link

Workshop

  • Ye W, Hu X, Liu T, et al. 5GNN: extrapolating 5G measurements through GNNs[C]//Proceedings of the 1st International Workshop on Graph Neural Networking. 2022: 36-41. Link Code
  • Giakatos D P, Kostoglou S, Sermpezis P, et al. Benchmarking graph neural networks for internet routing data[C]//Proceedings of the 1st International Workshop on Graph Neural Networking. 2022: 1-6. Link Code
  • Fernandes D M, Krolikowski J, Houidi Z B, et al. Cross-network transferable neural models for WLAN interference estimation[C]//Proceedings of the 1st International Workshop on Graph Neural Networking. 2022: 30-35. Link
  • Kiamari M, Krishnamachari B. Gcnscheduler: Scheduling distributed computing applications using graph convolutional networks[C]//Proceedings of the 1st International Workshop on Graph Neural Networking. 2022: 13-17. Link
  • Randall M, Belzarena P, Larroca F, et al. GROWS: improving decentralized resource allocation in wireless networks through graph neural networks[C]//Proceedings of the 1st International Workshop on Graph Neural Networking. 2022: 24-29. Link Code
  • Jaeger B, Helm M, Schwegmann L, et al. Modeling TCP performance using graph neural networks[C]//Proceedings of the 1st International Workshop on Graph Neural Networking. 2022: 18-23. Link Code (access required)
  • Wang T Y, Zhou H, Kannan R, et al. Throughput optimization in heterogeneous MIMO networks: a GNN-based approach[C]//Proceedings of the 1st International Workshop on Graph Neural Networking. 2022: 42-47. Link
  • Latif H, Paillissé J, Yang J, et al. Unveiling the potential of graph neural networks for BGP anomaly detection[C]//Proceedings of the 1st International Workshop on Graph Neural Networking. 2022: 7-12. Link

Preprint

  • Liu Q, Li X, Li Z, et al. Graph Reinforcement Learning Application to Co-operative Decision-Making in Mixed Autonomy Traffic: Framework, Survey, and Challenges[J]. arXiv preprint arXiv:2211.03005, 2022. Link Code
  • Mehrabi M, Masoudimansour W, Zhang Y, et al. Neighbor Auto-Grouping Graph Neural Networks for Handover Parameter Configuration in Cellular Network[J]. arXiv preprint arXiv:2301.03412, 2022. Link
  • Zhao Z, Radojicic B, Verma G, et al. Delay-aware Backpressure Routing Using Graph Neural Networks[J]. arXiv preprint arXiv:2211.10748, 2022. Link Code
  • Li B, Verma G, Segarra S. Graph-based Algorithm Unfolding for Energy-aware Power Allocation in Wireless Networks[J]. arXiv preprint arXiv:2201.11799, 2022. Link Code
  • Zhao J, Yang C. Graph Reinforcement Learning for Predictive Power Allocation to Mobile Users[J]. arXiv preprint arXiv:2203.03906, 2022. Link
  • Geyer F, Scheffler A, Bondorf S. Network Calculus with Flow Prolongation--A Feedforward FIFO Analysis enabled by ML[J]. arXiv preprint arXiv:2202.03004, 2022. Link
  • Xu X, Liu Y, Mu X, et al. Artificial Intelligence Enabled NOMA Towards Next Generation Multiple Access[J]. arXiv preprint arXiv:2206.04992, 2022. Link
  • Li H, Wang J, Wang Y. Edge Graph Neural Networks for Massive MIMO Detection[J]. arXiv preprint arXiv:2206.06979, 2022. Link
  • He H, Kosasihy A, Yu X, et al. Graph Neural Network Enhanced Approximate Message Passing for MIMO Detection[J]. arXiv preprint arXiv:2205.10620, 2022. Link
  • Kosasih A, Onasis V, Miloslavskaya V, et al. Graph Neural Network Aided MU-MIMO Detectors[J]. arXiv preprint arXiv:2206.09381, 2022. Link Code
  • Azeez S. Graph-based Deep Learning for Spatial Reuse Optimization in Dense WLAN Deployments[J]. 2022. Link
  • Lima V, Eisen M, Gatsis K, et al. Graph Reinforcement Learning for Wireless Control Systems: Large-Scale Resource Allocation over Interference Channels[J]. arXiv preprint arXiv:2201.09859, 2022. Link

2021

Journal

  • Shen Y, Shi Y, Zhang J, et al. Graph neural networks for scalable radio resource management: Architecture design and theoretical analysis[J]. IEEE Journal on Selected Areas in Communications, 2021, 39(1): 101-115. Link Code
  • Lee M, Yu G, Dai H. Decentralized Inference with Graph Neural Networks in Wireless Communication Systems[J]. IEEE Transactions on Mobile Computing, 2021. Link
  • Li N, Jia S, Li Q. Traffic Message Channel Prediction Based on Graph Convolutional Network[J]. IEEE Access, 2021, 9: 135423-135431. Link
  • Chowdhury A, Verma G, Rao C, et al. Unfolding wmmse using graph neural networks for efficient power allocation[J]. IEEE Transactions on Wireless Communications, 2021. Link Code
  • Zhang K, Zhao X, Li X, et al. Network Traffic Prediction via Deep Graph-Sequence Spatiotemporal Modeling Based on Mobile Virtual Reality Technology[J]. Wireless Communications and Mobile Computing, 2021, 2021. Link
  • Shao Y, Li R, Hu B, et al. Graph Attention Network-based Multi-agent Reinforcement Learning for Slicing Resource Management in Dense Cellular Network[J]. IEEE Transactions on Vehicular Technology, 2021, 70(10): 10792-10803. Link
  • Dong T, Zhuang Z, Qi Q, et al. Intelligent Joint Network Slicing and Routing via GCN-powered Multi-Task Deep Reinforcement Learning[J]. IEEE Transactions on Cognitive Communications and Networking, 2021. Link
  • Sun F, Wang P, Zhao J, et al. Mobile Data Traffic Prediction by Exploiting Time-Evolving User Mobility Patterns[J]. IEEE Transactions on Mobile Computing, 2021. Link
  • Pan C, Zhu J, Kong Z, et al. DC-STGCN: Dual-Channel Based Graph Convolutional Networks for Network Traffic Forecasting[J]. Electronics, 2021, 10(9): 1014. Link
  • Wu Y, Dai H N, Tang H. Graph neural networks for anomaly detection in industrial internet of things[J]. IEEE Internet of Things Journal, 2021. Link
  • Chen T, Zhang X, You M, et al. A GNN-Based Supervised Learning Framework for Resource Allocation in Wireless IoT Networks[J]. IEEE Internet of Things Journal, 2021, 9(3): 1712-1724. Link
  • Chen G, Wu J, Yang W, et al. Leveraging Graph Convolutional-LSTM for Energy Efficient Caching in Blockchain-based Green IoT[J]. IEEE Transactions on Green Communications and Networking, 2021. Link
  • Tang M, Cai S, Lau V K N. Over-the-Air-Aggregation with Multiple Shared Channels and Graph-based State Estimation for Industrial IoT Systems[J]. IEEE Internet of Things Journal, 2021. Link
  • Hu Z, Liu L, Yu H, et al. Using Graph Representation in Host-Based Intrusion Detection[J]. Security and Communication Networks, 2021, 2021. Link
  • Cheng Q, Wu C, Zhou S. Discovering Attack Scenarios via Intrusion Alert Correlation using Graph Convolutional Networks[J]. IEEE Communications Letters, 2021. Link
  • Soto P, Camelo M, Mets K, et al. ATARI: A Graph Convolutional Neural Network Approach for Performance Prediction in Next-Generation WLANs[J]. Sensors, 2021, 21(13): 4321. Link Data
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Conference

  • Nagaraj K, Starke A, McNair J. Glass: a graph learning approach for software defined network based smart grid ddos security[C]//ICC 2021-IEEE International Conference on Communications. IEEE, 2021: 1-6. Link
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  • Guo J, Yang C. Learning Power Control for Cellular Systems with Heterogeneous Graph Neural Network[C]//2021 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2021: 1-6. Link
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  • Chen T, You M, Zheng G, et al. Graph Neural Network Based Beamforming in D2D Wireless Networks[C]. The 25th International ITG Workshop on Smart Antennas (WSA), Nov. 2021, EURECOM, French Riviera. Link
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  • Zhao Z, Verma G, Rao C, et al. Distributed scheduling using graph neural networks[C]//ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2021: 4720-4724. Link Code
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  • Khan T A, Abbas K, Rivera J J D, et al. Applying RouteNet and LSTM to Achieve Network Automation: An Intent-based Networking Approach[C]//2021 22nd Asia-Pacific Network Operations and Management Symposium (APNOMS). IEEE, 2021: 254-257. Link
  • Siyu Q I, Shuopeng L I, Shaofu L I N, et al. Energy-Efficient VNF Deployment for Graph-Structured SFC Based on Graph Neural Network and Constrained Deep Reinforcement Learning[C]//2021 22nd Asia-Pacific Network Operations and Management Symposium (APNOMS). IEEE, 2021: 348-353. Link
  • Wang T, Fan Q, Li X, et al. Drl-sfcp: Adaptive service function chains placement with deep reinforcement learning[C]//ICC 2021-IEEE International Conference on Communications. IEEE, 2021: 1-6. Link Code
  • Yang Z, Gu R, Ji Y. Virtual Network Function Placement Based on Differentiated Weight Graph Convolutional Neural Network and Maximal Weight Matching[C]//2021 IEEE Symposium on Computers and Communications (ISCC). IEEE, 2021: 1-7. Link
  • Yeom S, Choi C, Kolekar S S, et al. Graph Convolutional Network based Link State Prediction[C]//2021 22nd Asia-Pacific Network Operations and Management Symposium (APNOMS). IEEE, 2021: 246-249. Link
  • Cui T, Gou G, Xiong G, et al. SIAMHAN: IPv6 Address Correlation Attacks on TLS Encrypted Traffic via Siamese Heterogeneous Graph Attention Network[C]//30th USENIX Security Symposium (USENIX Security 21). 2021: 4329-4346. Link
  • Liu T, Li P, Gu Y. Glint: Decentralized Federated Graph Learning with Traffic Throttling and Flow Scheduling[C]//2021 IEEE/ACM 29th International Symposium on Quality of Service (IWQOS). IEEE, 2021: 1-10. Link
  • Ranasinghe V, Rajatheva N, Latva-aho M. Graph Neural Network Based Access Point Selection for Cell-Free Massive MIMO Systems[C]. 2021 IEEE Global Communications Conference (GLOBECOM). IEEE, 2021: 01-06. Link
  • Pujol-Perich D, Suárez-Varela J, Xiao S, et al. NetXplain: Real-Time Explainability of Graph Neural Networks Applied to Computer Networks[C]. GNNSys workshop, 2021. Link
  • Zhu H, Gupta V, Ahuja S S, et al. Network planning with deep reinforcement learning[C]//Proceedings of the 2021 ACM SIGCOMM 2021 Conference. 2021: 258-271. Link Code
  • Bernárdez G, Suárez-Varela J, López A, et al. Is Machine Learning Ready for Traffic Engineering Optimization?[C]. IEEE ICNP 2021. Link
  • Li L, Jiang H, He H. Graph-based Multi-view Learning for Cooperative Spectrum Sensing[C]//2021 International Joint Conference on Neural Networks (IJCNN). IEEE, 2021: 1-7. Link
  • Orhan O, Swamy V N, Tetzlaff T, et al. Connection Management xAPP for O-RAN RIC: A Graph Neural Network and Reinforcement Learning Approach[C]. 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA). IEEE, 2021: 936-941. Link
  • Ren X, Zhang W, Bao L, et al. Deepqsc: A gnn and attention mechanism-based framework for qos-aware service composition[C]//2021 International Conference on Service Science (ICSS). IEEE, 2021: 76-83. Link
  • Le T T, Le Nguyen P, Binh H T T, et al. GCRINT: Network Traffic Imputation Using Graph Convolutional Recurrent Neural Network[C]//ICC 2021-IEEE International Conference on Communications. IEEE, 2021: 1-6. Link Code
  • Poularakis K, Qin Q, Le F, et al. Generalizable and Interpretable Deep Learning for Network Congestion Prediction[C]. IEEE International Conference on Network Protocols (ICNP), 2021. Link
  • Park J, Choi B, Lee C, et al. GRAF: a graph neural network based proactive resource allocation framework for SLO-oriented microservices[C]//Proceedings of the 17th International Conference on emerging Networking EXperiments and Technologies. 2021: 154-167. Link
  • Nikoloska I, Simeone O. Fast power control adaptation via meta-learning for random edge graph neural networks[C]//2021 IEEE 22nd International Workshop on Signal Processing Advances in Wireless Communications (SPAWC). IEEE, 2021: 146-150. Link Code (Empty)
  • Mai X, Fu Q, Chen Y. Packet routing with graph attention multi-agent reinforcement learning[C]//2021 IEEE Global Communications Conference (GLOBECOM). IEEE, 2021: 1-6. Link

Preprint

  • Nikoloska I, Simeone O. Black-box and modular meta-learning for power control via random edge graph neural networks[J]. arXiv preprint arXiv:2108.13178, 2021. Link
  • Zhang X, Zhang Z, Yang L. Joint User Association and Power Allocation in Heterogeneous Ultra Dense Network via Semi-Supervised Representation Learning[J]. arXiv preprint arXiv:2103.15367, 2021. Link
  • He S, Yuan J, An Z, et al. Joint User Scheduling and Beamforming Design for Multiuser MISO Downlink Systems[J]. arXiv preprint arXiv:2112.01738, 2021. Link
  • Naderializadeh N. Wireless Link Scheduling via Graph Representation Learning: A Comparative Study of Different Supervision Levels[J]. arXiv preprint arXiv:2110.01722, 2021. Link Code
  • Tekbıyık K, Kurt G K, Ekti A R, et al. Graph Attention Networks for Channel Estimation in RIS-assisted Satellite IoT Communications[J]. arXiv preprint arXiv:2104.00735, 2021. Link
  • Chang L, Branco P. Graph-based Solutions with Residuals for Intrusion Detection: the Modified E-GraphSAGE and E-ResGAT Algorithms[J]. arXiv preprint arXiv:2111.13597, 2021. Link
  • Liu M, Li J, Lu H. Routing in Small Satellite Networks: A GNN-based Learning Approach[J]. arXiv preprint arXiv:2108.08523, 2021. Link
  • Pang B, Fu Y, Ren S, et al. CGNN: Traffic Classification with Graph Neural Network[J]. arXiv preprint arXiv:2110.09726, 2021. Link
  • Shabka Z, Zervas G. Nara: Learning Network-Aware Resource Allocation Algorithms for Cloud Data Centres[J]. arXiv preprint arXiv:2106.02412, 2021. Link
  • Ding S, Zhang F, Luo X, et al. GCN-Geo: A Graph Convolution Network-based Fine-grained IP Geolocation Framework[J]. arXiv preprint arXiv:2112.10767, 2021. Link
  • Lv M, Dong C, Chen T, et al. A Heterogeneous Graph Learning Model for Cyber-Attack Detection[J]. arXiv preprint arXiv:2112.08986, 2021. Link
  • Shen Y, Zhang J, Letaief K B. How Neural Architectures Affect Deep Learning for Communication Networks?[J]. arXiv preprint arXiv:2111.02215, 2021. Link

2020

Journal

  • Yang Y, Zhang S, Gao F, et al. Graph Neural Network-Based Channel Tracking for Massive MIMO Networks[J]. IEEE Communications Letters, 2020, 24(8): 1747-1751. Link
  • Nakashima K, Kamiya S, Ohtsu K, et al. Deep reinforcement learning-based channel allocation for wireless lans with graph convolutional networks[J]. IEEE Access, 2020, 8: 31823-31834. Link
  • Eisen M, Ribeiro A. Optimal wireless resource allocation with random edge graph neural networks[J]. IEEE Transactions on Signal Processing, 2020, 68: 2977-2991. Link
  • Naderializadeh N, Eisen M, Ribeiro A. Wireless power control via counterfactual optimization of graph neural networks[C]//2020 IEEE 21st International Workshop on Signal Processing Advances in Wireless Communications (SPAWC). IEEE, 2020: 1-5. Link
  • Simsek M, Orhan O, Nassar M, et al. IAB Topology Design: A Graph Embedding and Deep Reinforcement Learning Approach[J]. IEEE Communications Letters, 2020. Link
  • Wang H, Wu Y, Min G, et al. A Graph Neural Network-based Digital Twin for Network Slicing Management[J]. IEEE Transactions on Industrial Informatics, 2020. Link
  • Zhu T, Chen X, Chen L, et al. GCLR: GNN-Based Cross Layer Optimization for Multipath TCP by Routing[J]. IEEE Access, 2020, 8: 17060-17070. Link
  • He K, Chen X, Wu Q, et al. Graph Attention Spatial-Temporal Network with Collaborative Global-Local Learning for Citywide Mobile Traffic Prediction[J]. IEEE Transactions on Mobile Computing, 2020. Link
  • Zhao D, Qin H, Song B, et al. A graph convolutional network-based deep reinforcement learning approach for resource allocation in a cognitive radio network[J]. Sensors, 2020, 20(18): 5216. Link
  • Yan Y, Zhang B, Li C, et al. Cooperative Caching and Fetching in D2D Communications-A Fully Decentralized Multi-Agent Reinforcement Learning Approach[J]. IEEE Transactions on Vehicular Technology, 2020, 69(12): 16095-16109. Link
  • Lee M, Yu G, Li G Y. Graph embedding based wireless link scheduling with few training samples[J]. IEEE Transactions on Wireless Communications, 2020. Link
  • Liu Y, Lu Y, Li X, et al. On dynamic service function chain reconfiguration in IoT networks[J]. IEEE Internet of Things Journal, 2020, 7(11): 10969-10984. Link
  • Geyer F, Bondorf S. Graph-based Deep Learning for Fast and Tight Network Calculus Analyses[J]. IEEE Transactions on Network Science and Engineering, 2020. Link
  • Zhao J, Qu H, Zhao J, et al. Spatiotemporal graph convolutional recurrent networks for traffic matrix prediction[J]. Transactions on Emerging Telecommunications Technologies, 2020, 31(11): e4056. Link
  • Li J, Sun P, Hu Y. Traffic modeling and optimization in datacenters with graph neural network[J]. Computer Networks, 2020, 181: 107528. Link
  • Rusek K, Suárez-Varela J, Almasan P, et al. RouteNet: Leveraging Graph Neural Networks for network modeling and optimization in SDN[J]. IEEE Journal on Selected Areas in Communications, 2020, 38(10): 2260-2270. Link
  • Sun P, Lan J, Li J, et al. Efficient flow migration for NFV with Graph-aware deep reinforcement learning[J]. Computer Networks, 2020, 183: 107575. Link
  • Yan Z, Ge J, Wu Y, et al. Automatic virtual network embedding: A deep reinforcement learning approach with graph convolutional networks[J]. IEEE Journal on Selected Areas in Communications, 2020, 38(6): 1040-1057. Link
  • Sun P, Lan J, Li J, et al. Combining Deep Reinforcement Learning With Graph Neural Networks for Optimal VNF Placement[J]. IEEE Communications Letters, 2020. Link
  • Do Xuan C, Dao M H, Nguyen H D. APT attack detection based on flow network analysis techniques using deep learning[J]. Journal of Intelligent & Fuzzy Systems, 2020, 39(3): 4785-4801. Link

Conference

  • Eisen M, Ribeiro A. Transferable Policies for Large Scale Wireless Networks with Graph Neural Networks[C]//ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2020: 5040-5044. Link
  • Zhao S, Jiang X, Jacobson G, et al. Cellular Network Traffic Prediction Incorporating Handover: A Graph Convolutional Approach[C]//2020 17th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON). IEEE, 2020: 1-9. Link
  • Rkhami A, Pham T A Q, Hadjadj-Aoul Y, et al. On the Use of Graph Neural Networks for Virtual Network Embedding[C]//2020 International Symposium on Networks, Computers and Communications (ISNCC). IEEE, 2020: 1-6. Link
  • Lee M, Yu G, Li G Y. Wireless Link Scheduling for D2D Communications with Graph Embedding Technique[C]//ICC 2020-2020 IEEE International Conference on Communications (ICC). IEEE, 2020: 1-6. Link
  • Fu J, Ma N, Ye M, et al. Wireless D2D Network Link Scheduling based on Graph Embedding[C]//2020 IEEE 92nd Vehicular Technology Conference (VTC2020-Fall). IEEE, 1-5. Link
  • Yang L, Gu X, Shi H. A Noval Satellite Network Traffic Prediction Method Based on GCN-GRU[C]//2020 International Conference on Wireless Communications and Signal Processing (WCSP). IEEE, 2020: 718-723. Link
  • He Z, Wang L, Ye H, et al. Resource Allocation based on Graph Neural Networks in Vehicular Communications[C]//GLOBECOM 2020-2020 IEEE Global Communications Conference. IEEE, 2020: 1-5. Link Code
  • Bahnasy M, Li F, Xiao S, et al. DeepBGP: A Machine Learning Approach for BGP Configuration Synthesis[C]//Proceedings of the Workshop on Network Meets AI & ML. 2020: 48-55. Link
  • Zhou J, Xu Z, Rush A M, et al. Automating Botnet Detection with Graph Neural Networks[C]. AutoML for Networking and Systems Workshop of MLSys 2020 Conference. Link Data
  • Suzuki T, Yasuda Y, Nakamura R, et al. On Estimating Communication Delays using Graph Convolutional Networks with Semi-Supervised Learning[C]//2020 International Conference on Information Networking (ICOIN). IEEE, 2020: 481-486. Link
  • Mo S, Wang Y, Xiao D, et al. Encrypted Traffic Classification Using Graph Convolutional Networks[C]//International Conference on Advanced Data Mining and Applications. Springer, Cham, 2020: 207-219. Link
  • Sun B, Yang W, Yan M, et al. An encrypted traffic classification method combining graph convolutional network and autoencoder[C]//2020 IEEE 39th International Performance Computing and Communications Conference (IPCCC). IEEE, 2020: 1-8. Link
  • Geyer F, Bondorf S. On the robustness of deep learning-predicted contention models for network calculus[C]//2020 IEEE Symposium on Computers and Communications (ISCC). IEEE, 2020: 1-7. Link
  • Xiao S, Mao H, Wu B, et al. Neural Packet Routing[C]//Proceedings of the Workshop on Network Meets AI & ML. 2020: 28-34. Link
  • Yang C, Zhou Z, Wen H, et al. MSTNN: A graph learning based method for the origin-destination traffic prediction[C]//ICC 2020-2020 IEEE International Conference on Communications (ICC). IEEE, 2020: 1-6. Link
  • Vinchoff C, Chung N, Gordon T, et al. Traffic Prediction in Optical Networks Using Graph Convolutional Generative Adversarial Networks[C]//2020 22nd International Conference on Transparent Optical Networks (ICTON). IEEE, 2020: 1-4. Link
  • Gui Y, Wang D, Guan L, et al. Optical Network Traffic Prediction Based on Graph Convolutional Neural Networks[C]//2020 Opto-Electronics and Communications Conference (OECC). IEEE, 2020: 1-3. Link
  • Sawada K, Kotani D, Okabe Y. Network Routing Optimization Based on Machine Learning Using Graph Networks Robust against Topology Change[C]//2020 International Conference on Information Networking (ICOIN). IEEE, 2020: 608-615. Link
  • Heo D N, Lange S, Kim H G, et al. Graph Neural Network based Service Function Chaining for Automatic Network Control[C]//2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS). IEEE, 2020: 7-12. Link
  • Rafiq A, Khan T A, Afaq M, et al. Service Function Chaining and Traffic Steering in SDN using Graph Neural Network[C]//2020 International Conference on Information and Communication Technology Convergence (ICTC). IEEE, 2020: 500-505. Link
  • Sun P, Lan J, Guo Z, et al. DeepMigration: Flow Migration for NFV with Graph-based Deep Reinforcement Learning[C]//ICC 2020-2020 IEEE International Conference on Communications (ICC). IEEE, 2020: 1-6. Link
  • Habibi F, Dolati M, Khonsari A, et al. Accelerating Virtual Network Embedding with Graph Neural Networks[C]//2020 16th International Conference on Network and Service Management (CNSM). IEEE, 2020: 1-9. Link
  • Kim H G, Park S, Heo D, et al. Graph Neural Network-based Virtual Network Function Deployment Prediction[C]//2020 16th International Conference on Network and Service Management (CNSM). IEEE, 2020: 1-7. Link
  • Kim H G, Park S, Lange S, et al. Graph neural network-based virtual network function management[C]//2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS). IEEE, 2020: 13-18. Link
  • Scotti A, Moghadam N N, Liu D, et al. Graph Neural Networks for Massive MIMO Detection[C]. ICML 2020 Workshop on Graph Representation Learning and Beyond (GRL+), 2020. Link
  • Mallick T, Kiran M, Mohammed B, et al. Dynamic graph neural network for traffic forecasting in wide area networks[C]//2020 IEEE International Conference on Big Data (Big Data). IEEE, 2020: 1-10. Link
  • Gao Z, Eisen M, Ribeiro A. Resource allocation via graph neural networks in free space optical fronthaul networks[C]//GLOBECOM 2020-2020 IEEE Global Communications Conference. IEEE, 2020: 1-6. Link

Preprint

  • Ferriol-Galmés M, Suárez-Varela J, Barlet-Ros P, et al. Applying Graph-based Deep Learning To Realistic Network Scenarios[J]. arXiv preprint arXiv:2010.06686, 2020. Link
  • Dong J, Chen S, Ha P Y J, et al. A DRL-based Multiagent Cooperative Control Framework for CAV Networks: a Graphic Convolution Q Network[J]. arXiv preprint arXiv:2010.05437, 2020. Link

2019

Journal

  • Fang L, Cheng X, Wang H, et al. Idle time window prediction in cellular networks with deep spatiotemporal modeling[J]. IEEE Journal on Selected Areas in Communications, 2019, 37(6): 1441-1454. Link
  • Geyer F. DeepComNet: Performance evaluation of network topologies using graph-based deep learning[J]. Performance Evaluation, 2019, 130: 1-16. Link
  • Zhuang Z, Wang J, Qi Q, et al. Toward greater intelligence in route planning: A graph-aware deep learning approach[J]. IEEE Systems Journal, 2019, 14(2): 1658-1669. Link

Conference

  • Eisen M, Ribeiro A. Large scale wireless power allocation with graph neural networks[C]//2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC). IEEE, 2019: 1-5. Link
  • Shen Y, Shi Y, Zhang J, et al. A graph neural network approach for scalable wireless power control[C]//2019 IEEE Globecom Workshops (GC Wkshps). IEEE, 2019: 1-6. Link Code
  • He K, Huang Y, Chen X, et al. Graph attention spatial-temporal network for deep learning based mobile traffic prediction[C]//2019 IEEE Global Communications Conference (GLOBECOM). IEEE, 2019: 1-6. Link
  • Geyer F, Schmid S. DeepMPLS: fast analysis of MPLS configurations using deep learning[C]//2019 IFIP Networking Conference (IFIP Networking). IEEE, 2019: 1-9. Link
  • Geyer F, Bondorf S. DeepTMA: Predicting effective contention models for network calculus using graph neural networks[C]//IEEE INFOCOM 2019-IEEE Conference on Computer Communications. IEEE, 2019: 1009-1017. Link
  • Suárez-Varela J, Carol-Bosch S, Rusek K, et al. Challenging the generalization capabilities of Graph Neural Networks for network modeling[C]//Proceedings of the ACM SIGCOMM 2019 Conference Posters and Demos. 2019: 114-115. Link
  • Badia-Sampera A, Suárez-Varela J, Almasan P, et al. Towards more realistic network models based on Graph Neural Networks[C]//Proceedings of the 15th International Conference on emerging Networking EXperiments and Technologies. 2019: 14-16. Link
  • Rusek K, Suárez-Varela J, Mestres A, et al. Unveiling the potential of Graph Neural Networks for network modeling and optimization in SDN[C]//Proceedings of the 2019 ACM Symposium on SDN Research. 2019: 140-151. Link
  • Jalodia N, Henna S, Davy A. Deep Reinforcement Learning for Topology-Aware VNF Resource Prediction in NFV Environments[C]//2019 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN). IEEE, 2019: 1-5. Link

2018

Journal

  • Rusek K, Chołda P. Message-passing neural networks learn little’s law[J]. IEEE Communications Letters, 2018, 23(2): 274-277. Link

2017

Journal

  • Mijumbi R, Hasija S, Davy S, et al. Topology-aware prediction of virtual network function resource requirements[J]. IEEE Transactions on Network and Service Management, 2017, 14(1): 106-120. Link

2016

Conference

  • Mijumbi R, Hasija S, Davy S, et al. A connectionist approach to dynamic resource management for virtualised network functions[C]//2016 12th International Conference on Network and Service Management (CNSM). IEEE, 2016: 1-9. Link

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

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