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:

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

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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

• 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

• 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

• Xu R, Wu G, Wang W, et al. Applying Self-supervised Learning to Network Intrusion Detection for Network Flows with Graph Neural Network[J]. arXiv preprint arXiv:2403.01501, 2024. Link Code
• 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
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• 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

• 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
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• 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
• Guo J, Yang C. A Size-Generalizable GNN for Learning Precoding[C]//2023 IEEE 98th Vehicular Technology Conference (VTC2023-Fall). IEEE, 2023: 1-6. Link
• Saheed K, Henna S. Heterogeneous Graph Transformer for Advanced Persistent Threat Classification in Wireless Networks[C]//2023 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN). IEEE, 2023: 15-20. Link
• Liao X, Sun H, Wang J, et al. Solving Distributed ACL Policies Under Complex Constraints with Graph Neural Networks[C]//2023 IEEE 31st International Conference on Network Protocols (ICNP). IEEE, 2023: 1-12. Link
• Rezazadeh F, Barrachina-Muñoz S, Zeydan E, et al. X-GRL: An Empirical Assessment of Explainable GNN-DRL in B5G/6G Networks[C]//2023 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN). IEEE, 2023: 172-174. Link
• Mehrabian A, Bahrami S, Wong V W S. A dynamic Bernstein graph recurrent network for wireless cellular traffic prediction[C]//ICC 2023-IEEE International Conference on Communications. IEEE, 2023: 3842-3847. Link
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• He P, Tang Y, Xu F, et al. Cellular Network Optimization Using Unfolding-Based Graph Neural Networks[C]//2023 IEEE 24th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC). IEEE, 2023: 551-555. Link
• Gao Z, Shao Y, Gündüz D, et al. Decentralized channel management in WLANs with graph neural networks[C]//ICC 2023-IEEE International Conference on Communications. IEEE, 2023: 3072-3077. Link
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• Sun H, Wu Q, She H, et al. DGL-Routing: One Routing Optimization Model Based on Deep Graph Learning[C]//2023 IEEE International Conference on Communications Workshops (ICC Workshops). IEEE, 2023: 891-896. Link
• Friji H, Olivereau A, Sarkiss M. Efficient Network Representation for GNN-Based Intrusion Detection[C]//International Conference on Applied Cryptography and Network Security. Cham: Springer Nature Switzerland, 2023: 532-554. Link
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• Hao X, Yeoh P L, Liu Y, et al. Graph Neural Network-Based Bandwidth Allocation for Secure Wireless Communications[C]//2023 IEEE International Conference on Communications Workshops (ICC Workshops). IEEE, 2023: 332-337. Link
• Tian Z, Zhang Z, Jin R. Graph-attention-Based decentralized edge learning for Non-IID data[C]//2023 IEEE International Conference on Communications Workshops (ICC Workshops). IEEE, 2023: 110-115. Link
• Zhang L, Shi H, Zhang K, et al. GraphMal: A Network Malicious Traffic Identification Method Based on Graph Neural Network[C]//2023 International Conference on Networking and Network Applications (NaNA). IEEE, 2023: 262-267. Link
• Wang Y, Li Y, Shi Q, et al. Learning cooperative beamforming with edge-update empowered graph neural networks[C]//ICC 2023-IEEE International Conference on Communications. IEEE, 2023: 5111-5116. Link
• Kim D, Song S. Power Allocation for Device-to-Device Interference Channel Using Truncated Graph Transformers[C]//2023 IEEE International Mediterranean Conference on Communications and Networking (MeditCom). IEEE, 2023: 109-114. Link Code
• Wang X, Cheng N, Fu L, et al. Scalable resource management for dynamic mec: An unsupervised link-output graph neural network approach[C]//2023 IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC). IEEE, 2023: 1-6. Link Code
• Du Q, Duan Y, Tao X, et al. Sketch Graph Representation for Multimedia Computational Communications: A Learning-Based Method[C]//ICC 2023-IEEE International Conference on Communications. IEEE, 2023: 553-558. Link
• Lai J, Yang F, Ying C, et al. Spatial-Temporal Correlation-Based Prediction Model for Node and Link Residual Resources in NFV Networks[C]//2023 International Conference on Networking and Network Applications (NaNA). IEEE, 2023: 256-261. Link
• Hou J, Nayak A. Spatial-Temporal Graph Attention-Based Multi-Agent Reinforcement Learning in Cooperative Edge Caching[C]//ICC 2023-IEEE International Conference on Communications. IEEE, 2023: 3078-3083. Link
• Perdomo J, Gutierrez-Estevez M A, Zhou C, et al. Towards a Wireless Network Digital Twin Model: A Heterogeneous Graph Neural Network Approach[C]//2023 IEEE International Conference on Communications Workshops (ICC Workshops). IEEE, 2023: 29-35. Link
• Tan Y, Wang J, Liu J. Virtual Network Embedding with Changeable Action Space: An Approach Based on Graph Neural Network and Reinforcement Learning[C]//ICC 2023-IEEE International Conference on Communications. IEEE, 2023: 3646-3651. Link
• Ye M, Liang X, Pan C, et al. Channel Estimation for mmWave Massive MIMO Systems Using Graph Neural Networks[C]//2023 IEEE/CIC International Conference on Communications in China (ICCC). IEEE, 2023: 1-5. Link
• Kim D, Song S. Power Allocation for Device-to-Device Interference Channel Using Truncated Graph Transformers[C]//2023 IEEE International Mediterranean Conference on Communications and Networking (MeditCom). IEEE, 2023: 109-114. Link Code
• Theodoropoulos T, Makris A, Psomakelis E, et al. GNOSIS: Proactive Image Placement Using Graph Neural Networks & Deep Reinforcement Learning[C]//2023 IEEE 16th International Conference on Cloud Computing (CLOUD). IEEE, 2023: 120-128. Link
• Zhang L, Tan L, Shi H, et al. Malicious Traffic Classification for IoT based on Graph Attention Network and Long Short-Term Memory Network[C]//2023 24st Asia-Pacific Network Operations and Management Symposium (APNOMS). IEEE, 2023: 54-59. Link
• Li L, Chen H, Yeom S, et al. Network State Prediction with Attention-Based Graph Convolutional Network[C]//2023 24st Asia-Pacific Network Operations and Management Symposium (APNOMS). IEEE, 2023: 215-218. Link
• El Kamel A. A GNN-Based Rate Limiting Framework for DDoS Attack Mitigation in Multi-Controller SDN[C]//2023 IEEE Symposium on Computers and Communications (ISCC). IEEE, 2023: 893-896. Link
• Guo Y, Wu Q, She H. A Routing Optimization Policy Using Graph Convolution Deep Reinforcement Learning[C]//2023 IEEE/CIC International Conference on Communications in China (ICCC). IEEE, 2023: 1-6. Link
• Bian Y, Sun Y, Zhai M, et al. Dependency-Aware Task Scheduling and Offloading Scheme based on Graph Neural Network For MEC-Assisted Network[C]//2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops). IEEE, 2023: 1-6. Link
• Carletti V, Foggia P, Vento M. Detecting Abnormal Communication Patterns in IoT Networks Using Graph Neural Networks[C]//International Workshop on Graph-Based Representations in Pattern Recognition. Cham: Springer Nature Switzerland, 2023: 127-138. Link
• Shen Z, Zhao X, Zou J. GinApp: An Inductive Graph Learning based Framework for Mobile Application Usage Prediction[C]//IEEE INFOCOM 2023-IEEE Conference on Computer Communications. IEEE, 2023: 1-10. Link
• Li Y, Zhou Z, Li R, et al. GoGDDoS: A Multi-Classifier for DDoS Attacks Using Graph Neural Networks[C]//2023 IEEE Symposium on Computers and Communications (ISCC). IEEE, 2023: 1462-1467. Link
• Liu J, Tang F, Chen L, et al. EAGLE: Heterogeneous GNN-based Network Performance Analysis[C]//2023 IEEE/ACM 31st International Symposium on Quality of Service (IWQoS). IEEE, 2023: 1-10. Link
• Li K, Ni W, Yuan X, et al. Exploring Graph Neural Networks for Joint Cruise Control and Task Offloading in UAV-enabled Mobile Edge Computing[C]//2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring). IEEE, 2023: 1-6. Link
• Rathore H, Griffith H. GNN-RL: Dynamic Reward Mechanism for Connected Vehicle Security using Graph Neural Networks and Reinforcement Learning[C]//2023 IEEE International Conference on Smart Computing (SMARTCOMP). IEEE, 2023: 201-203. Link
• Zhao B, Yang C. Learning Beamforming for RIS-aided Systems with Permutation Equivariant Graph Neural Networks[C]//2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring). IEEE, 2023: 1-5. Link
• Wei C, Xie G, Diao Z. Network Flow Based IoT Anomaly Detection Using Graph Neural Network[C]//International Conference on Knowledge Science, Engineering and Management. Cham: Springer Nature Switzerland, 2023: 432-445. Link
• Xie Y, Niu G, Pun M O, et al. Online Bipartite Matching for HAP Access in Space-Air-Ground Integrated Networks using Graph Neural Network-Enhanced Reinforcement Learning[C]. ICC Workshops, 2023. Link
• Saleem A, Raeiszadeh M, Ebrahimzadeh A, et al. A Deep Learning Approach for Root Cause Analysis in Real-Time IIoT Edge Networks[C]//NOMS 2023-2023 IEEE/IFIP Network Operations and Management Symposium. IEEE, 2023: 1-5. Link
• Rivera J J D, Sarwar M M S, Alam S, et al. An Intent-Based Networking mechanism: A study case for efficient path selection using Graph Neural Networks[C]//NOMS 2023-2023 IEEE/IFIP Network Operations and Management Symposium. IEEE, 2023: 1-6. Link
• Aykurt K, Kellerer W. Autonomous Network Management in Multi-Domain 6G Networks based on Graph Neural Networks[C]//9th IEEE International Conference on Network Softwarization (NetSoft), PhD Symposium. 2023. Link
• Li J, Zhou F, Li W, et al. Componentized Task Scheduling in Cloud-Edge Cooperative Scenarios Based on GNN-enhanced DRL[C]//NOMS 2023-2023 IEEE/IFIP Network Operations and Management Symposium. IEEE, 2023: 1-4. Link
• Moayyedi A, Ahmadi M, Salahuddin M A, et al. Generalizable GNN-based 5G RAN/MEC Slicing and Admission Control in Metropolitan Networks[C]//NOMS 2023-2023 IEEE/IFIP Network Operations and Management Symposium. IEEE, 2023: 1-9. Link
• Fawaz H, Houidi O, Zeghlache D, et al. Graph Convolutional Reinforcement Learning for Load Balancing and Smart Queuing[C]//2023 IFIP Networking Conference (IFIP Networking). IEEE, 2023: 1-9. Link
• Zhang L, Yin B, Wang Q, et al. Graph Neural Network-based Delay Prediction Model Enhanced by Network Calculus[C]//2023 IFIP Networking Conference (IFIP Networking). IEEE, 2023: 1-7. Link
• Chawla A, Bosneag A M, Dalgkitsis A. Graph-based Interpretable Anomaly Detection Framework for Network Slice Management in Beyond 5G Networks[C]//NOMS 2023-2023 IEEE/IFIP Network Operations and Management Symposium. IEEE, 2023: 1-6. Link
• Bouton M, Jeong J, Outes J, et al. Multi-agent Reinforcement Learning with Graph Q-Networks for Antenna Tuning[C]//NOMS 2023-2023 IEEE/IFIP Network Operations and Management Symposium. IEEE, 2023: 1-7. Link
• Barsellotti L, De Marinis L, Cugini F, et al. FTG-Net: Hierarchical Flow-to-Traffic Graph Neural Network for DDoS Attack Detection[C]//2023 IEEE 24th International Conference on High Performance Switching and Routing (HPSR). IEEE, 2023: 173-178. Link
• Peng Y, Guo Y, Hao R, et al. Network Traffic Prediction with Attention-based Spatial-Temporal Graph Network[C]//2023 IEEE 24th International Conference on High Performance Switching and Routing (HPSR). IEEE, 2023: 153-158. Link
• Chen Y, Cao H, Zhou Y, et al. A GCN-GRU Based End-to-End LEO Satellite Network Dynamic Topology Prediction Method[C]//2023 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2023: 1-6. Link
• Pang B, Fu Y, Ren S, et al. A Multi-Modal Approach For Context-Aware Network Traffic Classification[C]//ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2023: 1-5. Link
• Zhao Z, Radojicic B, Verma G, et al. Delay-Aware Backpressure Routing Using Graph Neural Networks[C]//ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2023: 1-5. Link Code
• Abouamer M S, Mitran P. Flexible Resource Allocation in IRS-assisted Systems using Hypernetworks[C]//2023 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2023: 1-6. Link
• Lu X, Zhang X, Lio P. GAT-DNS: DNS Multivariate Time Series Prediction Model Based on Graph Attention Network[C]//Companion Proceedings of the ACM Web Conference 2023. 2023: 127-131. Link
• He H, Kosasih A, Yu X, et al. GNN-Enhanced Approximate Message Passing for Massive/Ultra-Massive MIMO Detection[C]//2023 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2023: 1-6. Link
• Mo C T, Chen J H, Liao W. Graph Convolutional Network Augmented Deep Reinforcement Learning for Dependent Task Offloading in Mobile Edge Computing[C]//2023 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2023: 1-6. Link
• Wang G, Cheng P, Chen Z, et al. Inverse Reinforcement Learning with Graph Neural Networks for IoT Resource Allocation[C]//ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2023: 1-5. Link
• Xu X, Chen H, Simsarian J E, et al. Optical Network Diagnostics Using Graph Neural Networks and Natural Language Processing[C]//Optical Fiber Communication Conference. Optica Publishing Group, 2023: M3G. 5. Link
• Chen X, Chuai G, Zhang K, et al. Spatial-temporal Cellular Traffic Prediction: A Novel Method Based on Causality and Graph Attention Network[C]//2023 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2023: 1-6. Link
• Shrestha S, Fu X, Hong M. Towards efficient and optimal joint beamforming and antenna selection: A machine learning approach[C]//ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2023: 1-5. Link Code
• Xie Z, Xu H, Chen W, et al. Unsupervised Anomaly Detection on Microservice Traces through Graph VAE[C]//Proceedings of the ACM Web Conference 2023. 2023: 2874-2884. Link Code
• Liu M, Huang C, Di Renzo M, et al. Cooperative Beamforming and RISs Association for Multi-RISs Aided Multi-Users MmWave MIMO Systems through Graph Neural Networks[C]. ICC, 2023. Link
• Zhang H, Yu L, Xiao X, et al. TFE-GNN: A Temporal Fusion Encoder Using Graph Neural Networks for Fine-grained Encrypted Traffic Classification[C]//Proceedings of the ACM Web Conference 2023. 2023: 2066-2075. Link
• Abode D, Adeogun R, Berardinelli G. Power Control for 6G Industrial Wireless Subnetworks: A Graph Neural Network Approach[C]//2023 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2023: 1-6. Link Code
• Kisanga P, Woungang I, Traore I, et al. Network Anomaly Detection Using a Graph Neural Network[C]//2023 International Conference on Computing, Networking and Communications (ICNC). IEEE, 2023: 61-65. Link
• Ge Z, Hou J, Nayak A. Forecasting SDN End-to-End Latency Using Graph Neural Network[C]//2023 International Conference on Information Networking (ICOIN). IEEE, 2023: 293-298. Link
• Perera T, Alapallu S, Fang Y, et al. Flex-Net: A Graph Neural Network Approach to Resource Management in Flexible Duplex Networks[C]//2023 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2023: 1-6. Link Code

Preprint

• Hao X, She C, Yeoh P L, et al. Hybrid-Task Meta-Learning: A Graph Neural Network Approach for Scalable and Transferable Bandwidth Allocation[J]. arXiv preprint arXiv:2401.10253, 2023. Link
• Abode D, Adeogun R, Salaün L, et al. Unsupervised Graph-based Learning Method for Sub-band Allocation in 6G Subnetworks[J]. arXiv preprint arXiv:2401.00950, 2023. Link
• Mourya S, Reddy P, Amuru S D, et al. Spectral Temporal Graph Neural Network for massive MIMO CSI Prediction[J]. arXiv preprint arXiv:2312.02159, 2023. Link Code
• Zhao Z, Perazzone J, Verma G, et al. Congestion-aware Distributed Task Offloading in Wireless Multi-hop Networks Using Graph Neural Networks[J]. arXiv preprint arXiv:2312.02471, 2023. Link
• Li X, Chen M, Liu Y, et al. Graph Neural Networks for Joint Communication and Sensing Optimization in Vehicular Networks[J]. arXiv preprint arXiv:2302.02878, 2023. Link
• Güemes-Palau C, Galmés M F, Cabellos-Aparicio A, et al. Building a Graph-based Deep Learning network model from captured traffic traces[J]. arXiv preprint arXiv:2310.11889, 2023. Link
• Zhu J, Li R, Chen X, et al. Semantics-enhanced Temporal Graph Networks for Content Caching and Energy Saving[J]. arXiv preprint arXiv:2301.12355, 2023. Link
• Skocaj M, Rivera P E I, Verdone R, et al. Uplink Scheduling in Federated Learning: an Importance-Aware Approach via Graph Representation Learning[J]. arXiv preprint arXiv:2301.11903, 2023. Link
• Das S, NaderiAlizadeh N, Ribeiro A. Learning State-Augmented Policies for Information Routing in Communication Networks[J]. arXiv preprint arXiv:2310.00248, 2023. Link
• Li J, Ye M, Huang L, et al. An Intelligent SDWN Routing Algorithm Based on Network Situational Awareness and Deep Reinforcement Learning[J]. arXiv preprint arXiv:2305.10441, 2023. Link
• Kang C, Woo J, Hong J W K. Bitcoin Double-Spending Attack Detection using Graph Neural Network[J]. arXiv preprint arXiv:2304.13935, 2023. Link
• Almasan P, Suárez-Varela J, Lutu A, et al. Enhancing 5G Radio Planning with Graph Representations and Deep Learning[J]. arXiv preprint arXiv:2309.03603, 2023. Link
• Zhou H, Kannan R, Swami A, et al. HTNet: Dynamic WLAN Performance Prediction using Heterogenous Temporal GNN[J]. arXiv preprint arXiv:2304.10013, 2023. Link Code
• Chen Y, Shi Z, Wang H, et al. Graph Convolutional Network Enabled Power-Constrained HARQ Strategy for URLLC[J]. arXiv preprint arXiv:2308.02131, 2023. Link
• Bernárdez G, Suárez-Varela J, Shi X, et al. GraphCC: A Practical Graph Learning-based Approach to Congestion Control in Datacenters[J]. arXiv preprint arXiv:2308.04905, 2023. Link
• Zhao M, Fink O. Dynamic Graph Attention for Anomaly Detection in Heterogeneous Sensor Networks[J]. arXiv preprint arXiv:2307.03761, 2023. Link
• Liu Z, Huang L, Gao Z, et al. GA-DRL: Graph Neural Network-Augmented Deep Reinforcement Learning for DAG Task Scheduling over Dynamic Vehicular Clouds[J]. arXiv preprint arXiv:2307.00777, 2023. Link
• Yang H, Cheng N, Sun R, et al. Knowledge-Driven Resource Allocation for D2D Networks: A WMMSE Unrolled Graph Neural Network Approach[J]. arXiv preprint arXiv:2307.05882, 2023. Link
• Ma M. Multi-Task Offloading via Graph Neural Networks in Heterogeneous Multi-access Edge Computing[J]. arXiv preprint arXiv:2306.10232, 2023. Link
• Chowdhury A, Verma G, Swami A, et al. Deep Graph Unfolding for Beamforming in MU-MIMO Interference Networks[J]. arXiv preprint arXiv:2304.00446, 2023. Link Code
• Krishnan S, Park J, Sagar S, et al. Federated Graph Learning for Low Probability of Detection in Wireless Ad-Hoc Networks[J]. arXiv preprint arXiv:2306.01143, 2023. Link
• Mourya S, Reddy P, Amuru S D, et al. Graph Neural Networks-Based User Pairing in Wireless Communication Systems[J]. arXiv preprint arXiv:2306.00717, 2023. Link
• Li B, Perazzone J, Swami A, et al. Learning to Transmit with Provable Guarantees in Wireless Federated Learning[J]. arXiv preprint arXiv:2304.09329, 2023. Link Code
• Chen L, Zhu J, Evans J. Accelerating Graph Neural Networks via Edge Pruning for Power Allocation in Wireless Networks[J]. arXiv preprint arXiv:2305.12639, 2023. Link
• Li J, Ye M, Huang L, et al. An Intelligent SDWN Routing Algorithm Based on Network Situational Awareness and Deep Reinforcement Learning[J]. arXiv preprint arXiv:2305.10441, 2023. Link Code
• Du J, Luo T. Digital Twin Graph: Automated Domain-Agnostic Construction, Fusion, and Simulation of IoT-Enabled World[J]. arXiv preprint arXiv:2304.10018, 2023. Link
• Chen L, Zhu J, Evans J. Graph Neural Networks for Power Allocation in Wireless Networks with Full Duplex Nodes[J]. arXiv preprint arXiv:2303.16113, 2023. Link
• Zhou H, Kannan R, Swami A, et al. HTNet: Dynamic WLAN Performance Prediction using Heterogenous Temporal GNN[J]. arXiv preprint arXiv:2304.10013, 2023. Link Code
• Jin Y, Daoutis M, Girdzijauskas S, et al. Learning Cellular Coverage from Real Network Configurations using GNNs[J]. arXiv preprint arXiv:2304.10328, 2023. Link Code
• Paul R, Cohen K, Kedar G. Multi-Flow Transmission in Wireless Interference Networks: A Convergent Graph Learning Approach[J]. arXiv preprint arXiv:2303.15544, 2023. Link
• Zhu J, Li R, Chen X, et al. Semantics-enhanced Temporal Graph Networks for Content Caching and Energy Saving[J]. arXiv preprint arXiv:2301.12355, 2023. Link
• Xiao B, Li R, Wang F, et al. Stochastic Graph Neural Network-based Value Decomposition for MARL in Internet of Vehicles[J]. arXiv preprint arXiv:2303.13213, 2023. Link
• He H, Yu X, Zhang J, et al. Message Passing Meets Graph Neural Networks: A New Paradigm for Massive MIMO Systems[J]. arXiv preprint arXiv:2302.06896, 2023. Link

2022

Journal

• Li W, Wang H, Zhang X, et al. Security service function chain based on graph neural network[J]. Information, 2022, 13(2): 78. Link
• NaderiAlizadeh N, Eisen M, Ribeiro A. State-Augmented Learnable Algorithms for Resource Management in Wireless Networks[J]. IEEE Transactions on Signal Processing, 2022, 70: 5898-5912. Link Code
• Zhao Z, Verma G, Rao C, et al. Link scheduling using graph neural networks[J]. IEEE Transactions on Wireless Communications, 2022. Link Code
• Zhao X, Wu C. Large-scale Machine Learning Cluster Scheduling via Multi-agent Graph Reinforcement Learning[J]. IEEE Transactions on Network and Service Management, 2022. Link
• Chen J, Xiao W, Li X, et al. A routing optimization method for software-defined optical transport networks based on ensembles and reinforcement learning[J]. Sensors, 2022, 22(21): 8139. Link
• Bernárdez G, Suárez-Varela J, López A, et al. MAGNNETO: A Graph Neural Network-based Multi-Agent system for Traffic Engineering[J]. IEEE Transactions on Cognitive Communications and Networking, 2023. Link Code
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• Qiu R, Bao J, Li Y, et al. Virtual network function deployment algorithm based on graph convolution deep reinforcement learning[J]. The Journal of Supercomputing, 2022: 1-22. Link
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• He S, Xiong S, An Z, et al. An Unsupervised Deep Unrolling Framework for Constrained Optimization Problems in Wireless Networks[J]. IEEE Transactions on Wireless Communications, 2022. Link
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• Xu L, Huang Y C, Xue Y, et al. Deep Reinforcement Learning-based Routing and Spectrum Assignment of EONs by Exploiting GCN and RNN for Feature Extraction[J]. Journal of Lightwave Technology, 2022. Link
• Li K, Ni W, Yuan X, et al. Deep Graph-based Reinforcement Learning for Joint Cruise Control and Task Offloading for Aerial Edge Internet-of-Things (EdgeIoT)[J]. IEEE Internet of Things Journal, 2022. Link
• Lan J, Lu J Z, Wan G G, et al. E-minBatch GraphSAGE: An Industrial Internet Attack Detection Model[J]. Security and Communication Networks, 2022, 2022. Link
• Feng Y, Chen J, Liu Z, et al. Full Graph Autoencoder for One-Class Group Anomaly Detection of IIoT System[J]. IEEE Internet of Things Journal, 2022. Link
• Lee J, Cheng Y, Niyato D, et al. Intelligent Resource Allocation in Joint Radar-Communication With Graph Neural Networks[J]. IEEE Transactions on Vehicular Technology, 2022, 71(10): 11120-11135. Link
• Zhang Y, Yang C, Huang K, et al. Intrusion detection of industrial internet-of-things based on reconstructed graph neural networks[J]. IEEE Transactions on Network Science and Engineering, 2022. Link Code
• 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
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• 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
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• 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
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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
• Shen M, Zhang J, Zhu L, et al. Accurate Decentralized Application Identification via Encrypted Traffic Analysis Using Graph Neural Networks[J]. IEEE Transactions on Information Forensics and Security, 2021, 16: 2367-2380. Link
• Li B, Zhu Z. GNN-based Hierarchical Deep Reinforcement Learning for NFV-Oriented Online Resource Orchestration in Elastic Optical DCIs[J]. Journal of Lightwave Technology, 2021. Link
• Tian X, Li B, Gu R, et al. Reconfiguring multicast sessions in elastic optical networks adaptively with graph-aware deep reinforcement learning[J]. Journal of Optical Communications and Networking, 2021, 13(11): 253-265. Link
• Cao Y, Jiang H, Deng Y, et al. Detecting and Mitigating DDoS Attacks in SDN Using Spatial-Temporal Graph Convolutional Network[J]. IEEE Transactions on Dependable and Secure Computing, 2021. Link
• Swaminathan A, Chaba M, Sharma D K, et al. GraphNET: Graph Neural Networks for routing optimization in Software Defined Networks[J]. Computer Communications, 2021, 178: 169-182. Link
• Park M, Lee Y, Yeom I, et al. Gemma: Reinforcement Learning-Based Graph Embedding and Mapping for Virtual Network Applications[J]. IEEE Access, 2021, 9: 105463-105476. Link
• Xie Y, Huang L, Kong Y, et al. Virtualized Network Function Forwarding Graph Placing in sdn and nfv-Enabled iot Networks: A Graph Neural Network Assisted Deep Reinforcement Learning Method[J]. IEEE Transactions on Network and Service Management, 2021. Link
• Zhang P, Wang C, Kumar N, et al. Dynamic Virtual Network Embedding Algorithm based on Graph Convolution Neural Network and Reinforcement Learning[J]. IEEE Internet of Things Journal, 2021. Link
• Kim H G, Park S, Lange S, et al. Graph neural network‐based virtual network function deployment optimization[J]. International Journal of Network Management, 2021: e2164. 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, 8(19): 14638-14657. Link
• Jiang T, Cheng H V, Yu W. Learning to reflect and to beamform for intelligent reflecting surface with implicit channel estimation[J]. IEEE Journal on Selected Areas in Communications, 2021, 39(7): 1931-1945. Link Code
• Lv S, Yi F, He P, et al. QoS Prediction of Web Services Based on a Two-Level Heterogeneous Graph Attention Network[J]. IEEE Access, 2021, 10: 1871-1880. Link
• Guan L, Zhang M, Gui Y, et al. AI-assisted intent-based traffic grooming in a dynamically shared 5g optical fronthaul network[J]. Optics Express, 2021, 29(15): 23113-23130. Link
• Xu X, Chen Q, Mu X, et al. Graph-Embedded Multi-Agent Learning for Smart Reconfigurable THz MIMO-NOMA Networks[J]. IEEE Journal on Selected Areas in Communications, 2021, 40(1): 259-275. Link
• Lee H, Lee S H, Quek T Q S. Learning Autonomy in Management of Wireless Random Networks[J]. IEEE Transactions on Wireless Communications, 2021. Link
• Leng L, Li J, Shi H, et al. Graph convolutional network-based reinforcement learning for tasks offloading in multi-access edge computing[J]. Multimedia Tools and Applications, 2021, 80(19): 29163-29175. Link
• Mai T L, Navet N. Deep learning to predict the feasibility of priority-based Ethernet network configurations[J]. ACM Transactions on Cyber-Physical Systems (TCPS), 2021, 5(4): 1-26. Link
• Chen J, Wu Z. Dynamic computation offloading with energy harvesting devices: a graph-based deep reinforcement learning approach[J]. IEEE Communications Letters, 2021, 25(9): 2968-2972. Link
• Singh A, Sharma S, Gumaste A, et al. Grafnet: Using Graph Neural Networks to Create Table-Less Routers[J]. IEEE Transactions on Network Science and Engineering, 2021. Link
• Tekbıyık K, Yurduseven O, Kurt G K. Graph Attention Network-Based Single-Pixel Compressive Direction of Arrival Estimation[J]. IEEE Communications Letters, 2021. Link

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
• Li B, Verma G, Rao C, et al. Energy-Efficient Power Allocation in Wireless Networks using Graph Neural Networks[C]//2021 55th Asilomar Conference on Signals, Systems, and Computers. IEEE, 2021: 732-736. Link
• Chowdhury A, Verma G, Rao C, et al. Efficient power allocation using graph neural networks and deep algorithm unfolding[C]//ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2021: 4725-4729. Link Code
• Shen Y, Zhang J, Song S H, et al. AI Empowered Resource Management for Future Wireless Networks[C]. Meditcom 2021. Link
• Tekbıyık K, Kurt G K, Huang C, et al. Channel Estimation for Full-Duplex RIS-assisted HAPS Backhauling with Graph Attention Networks[C]. ICC 2021-2021 IEEE International Conference on Communications. IEEE, 2021. Link
• Shao Y, Li R, Zhao Z, et al. Graph Attention Network-based DRL for Network Slicing Management in Dense Cellular Networks[C]//2021 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2021: 1-6. Link
• 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
• Hou K, Xu Q, Zhang X, et al. User Association and Power Allocation Based on Unsupervised Graph Model in Ultra-Dense Network[C]//2021 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2021: 1-6. Link
• Rkhami A, Hadjadj-Aoul Y, Outtagarts A. Learn to improve: A novel deep reinforcement learning approach for beyond 5G network slicing[C]//2021 IEEE 18th Annual Consumer Communications & Networking Conference (CCNC). IEEE, 2021: 1-6. Link
• 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
• Zhang X, Zhao H, Xiong J, et al. Scalable Power Control/Beamforming in Heterogeneous Wireless Networks with Graph Neural Networks[C]//GLOBECOM 2021-2021 IEEE Global Communications Conference. IEEE, 2021. Link
• 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
• Sambamoorthy R, Mandalapu J, Peruru S S, et al. Graph Neural Network Based Scheduling: Improved Throughput Under a Generalized Interference Model[C]//EAI International Conference on Performance Evaluation Methodologies and Tools. Springer, Cham, 2021: 144-153. Link
• Yanyan Z, Zeyu L, Baocong W. Graph convolution network deep reinforcement learning approach based on manifold regularization in cognitive radio network[C]//2021 International Wireless Communications and Mobile Computing (IWCMC). IEEE, 2021: 1275-1280. Link
• Wang H, Ran Y, Zhao L, et al. GRouting: Dynamic Routing for LEO Satellite Networks with Graph-based Deep Reinforcement Learning[C]//2021 4th International Conference on Hot Information-Centric Networking (HotICN). IEEE, 2021: 123-128. Link
• Liu J, Xiao Y, Li Y, et al. Spatio-temporal Modeling for Large-scale Vehicular Networks Using Graph Convolutional Networks[C]. ICC 2021-2021 IEEE International Conference on Communications (ICC). IEEE, 2021. Link
• Zheng H, Ding X, Wang Y, et al. Attention Based Spatial-Temporal Graph Convolutional Networks for RSU Communication Load Forecasting[C]//International Conference on Collaborative Computing: Networking, Applications and Worksharing. Springer, Cham, 2021: 99-114. Link
• Yang Y, Wang L. LGANet: Local Graph Attention Network for Peer-to-Peer Botnet Detection[C]//2021 3rd International Conference on Advances in Computer Technology, Information Science and Communication (CTISC). IEEE, 2021: 31-36. Link
• Huoh T L, Luo Y, Zhang T. Encrypted Network Traffic Classification Using a Geometric Learning Model[C]//2021 IFIP/IEEE International Symposium on Integrated Network Management (IM). IEEE, 2021: 376-383. Link
• Busch J, Kocheturov A, Tresp V, et al. NF-GNN: Network Flow Graph Neural Networks for Malware Detection and Classification[C]. 33rd International Conference on Scientific and Statistical Database Management (SSDBM 2021), 2021. Link
• Pham T D, Ho T L, Truong-Huu T, et al. MAppGraph: Mobile-App Classification on Encrypted Network Traffic using Deep Graph Convolution Neural Networks[C]//Annual Computer Security Applications Conference. 2021: 1025-1038. Link Code and Data
• Mai T L, Navet N. Improvements to Deep-Learning-based Feasibility Prediction of Switched Ethernet Network Configurations[C]//The 29th International Conference on Real-Time Networks and Systems (RTNS2021). 2021. Link
• Kong Y, Petrov D, Räisänen V, et al. Path-Link Graph Neural Network for IP Network Performance Prediction[C]//2021 IFIP/IEEE International Symposium on Integrated Network Management (IM). IEEE, 2021: 170-177. Link
• Qin L, Wei W, Ma Y. FlowDiviner: Spatio-Temporal Network Traffic Prediction Method Based on Graph Neural Network[C]. 5th Asia-Pacific Workshop on Networking (APNet 2021). Link
• Yao Z, Xu Q, Chen Y, et al. Internet Traffic Forecasting using Temporal-Topological Graph Convolutional Networks[C]//2021 International Joint Conference on Neural Networks (IJCNN). IEEE, 2021: 1-8. Link
• Zhang K, Xu X, Fu C, et al. Modeling Data Center Networks with Message Passing Neural Network and Multi-task Learning[C]//International Conference on Neural Computing for Advanced Applications. Springer, Singapore, 2021: 96-112. Link
• Bao B, Yang H, Wan Y, et al. Node-Oriented Traffic Prediction and Scheduling Based on Graph Convolutional Network in Metro Optical Networks[C]//Optical Fiber Communication Conference. Optical Society of America, 2021: F2G. 2. Link
• Wang C, Yoshikane N, Tsuritani T. Usage of a Graph Neural Network for Large-Scale Network Performance Evaluation[C]//2021 International Conference on Optical Network Design and Modeling (ONDM). IEEE, 2021: 1-5. Link
• 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