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Analyzing the Traffic of MANETs using Graph Neural Networks

arXiv 2212.08923 ↗First posted 17 Dec 2022cs.LG cs.NIcited by 1

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Abstract (arXiv)

Graph Neural Networks (GNNs) have been taking role in many areas, thanks to their expressive power on graph-structured data. On the other hand, Mobile Ad-Hoc Networks (MANETs) are gaining attention as network technologies have been taken to the 5G level. However, there is no study that evaluates the efficiency of GNNs on MANETs. In this study, we aim to fill this absence by implementing a MANET dataset in a popular GNN framework, i.e., PyTorch Geometric; and show how GNNs can be utilized to analyze the traffic of MANETs. We operate an edge prediction task on the dataset with GraphSAGE (SAG) model, where SAG model tries to predict whether there is a link between two nodes. We construe several evaluation metrics to measure the performance and efficiency of GNNs on MANETs. SAG model showed 82.1 accuracy on average in the experiments.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 11 of its 21 references that are in the map. First posted on arXiv 17 Dec 2022.

Builds on

11 of 21 references.

References · 11

  1. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,361
  2. 2017Graph Attention Networkscited by 8,923
  3. 2017Inductive Representation Learning on Large Graphscited by 6,320
  4. 2018How Powerful are Graph Neural Networks?cited by 4,393
  5. 2017Neural Message Passing for Quantum Chemistrycited by 3,487
  6. 2019Fast Graph Representation Learning with PyTorch Geometriccited by 2,434
  7. 2019A Context-Aware Citation Recommendation Model with BERT and Graph Convolutional Networkscited by 29
  8. 2019Unveiling the potential of Graph Neural Networks for network modeling and optimization in SDNcited by 27
  9. 2020Pooling Regularized Graph Neural Network for fMRI Biomarker Analysiscited by 25
  10. 2015Gunrock: A High-Performance Graph Processing Library on the GPUcited by 14
  11. 2021The Graph Neural Networking Challenge: A Worldwide Competition for Education in AI/ML for Networkscited by 5

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Citing papers per year: 2024: 1.

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  1. 2024Survey of Graph Neural Network for Internet of Things and NextG Networkscited by 4