Towards Digital Twin Oriented Modelling of Complex Networked Systems and Their Dynamics: A Comprehensive Survey
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Abstract (arXiv)
This paper aims to provide a comprehensive critical overview on how entities and their interactions in Complex Networked Systems (CNS) are modelled across disciplines as they approach their ultimate goal of creating a Digital Twin (DT) that perfectly matches the reality. We propose a new framework to conceptually compare diverse existing modelling paradigms from different perspectives and create unified assessment criteria to assess their respective capabilities of reaching such an ultimate goal. Using the proposed criteria, we also appraise how far the reviewed current state-of-the-art approaches are from the idealised DTs. We also identify and propose potential directions and ways of building a DT-orientated CNS based on the convergence and integration of CNS and DT utilising a variety of cross-disciplinary techniques.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 69 of its 372 references that are in the map. First posted on arXiv 15 Feb 2022.
Builds on
69 of 372 references.
References · 69
- 2016node2vec: Scalable Feature Learning for Networkscited by 1,913
- 2014DeepWalk: Online Learning of Social Representationscited by 1,543
- 2017Towards A Rigorous Science of Interpretable Machine Learningcited by 1,400
- 2017Representation Learning on Graphs: Methods and Applicationscited by 456
- 2019Federated Learning in Mobile Edge Networks: A Comprehensive Surveycited by 407
- 2017A Comprehensive Survey of Graph Embedding: Problems, Techniques and Applicationscited by 260
- 2021A Comprehensive Survey on Graph Anomaly Detection with Deep Learningcited by 230
- 2014Graph-based Anomaly Detection and Description: A Surveycited by 182
- 2017A Survey on Network Embeddingcited by 142
- 2020Foundations and modelling of dynamic networks using Dynamic Graph Neural Networks: A surveycited by 123
- 2017Network Representation Learning: A Surveycited by 101
- 2019Hierarchical Federated Learning Across Heterogeneous Cellular Networkscited by 98
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- 2019GMNN: Graph Markov Neural Networkscited by 82
- 2020A Probabilistic Graphical Model Foundation for Enabling Predictive Digital Twins at Scalecited by 58
- 2020A Tutorial on Learning With Bayesian Networkscited by 56
- 2013Spectral redemption: clustering sparse networkscited by 54
- 2018N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classificationcited by 54
- 2018GC-LSTM: Graph Convolution Embedded LSTM for Dynamic Link Predictioncited by 47
- 2019GCN-GAN: A Non-linear Temporal Link Prediction Model for Weighted Dynamic Networkscited by 40
- 2017Jointly Attentive Spatial-Temporal Pooling Networks for Video-based Person Re-Identificationcited by 39
- 2018Scale-free networks are rarecited by 39
- 2013Clustering and Community Detection in Directed Networks: A Surveycited by 38
- 2021Hop-Count Based Self-Supervised Anomaly Detection on Attributed Networkscited by 31
- 2020Multi-level Graph Convolutional Networks for Cross-platform Anchor Link Predictioncited by 30
- 2020Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networkscited by 30
- 2020Low-latency Federated Learning and Blockchain for Edge Association in Digital Twin empowered 6G Networkscited by 30
- 2019Community detection in node-attributed social networks: a surveycited by 24
- 2013Bayesian Models of Graphs, Arrays and Other Exchangeable Random Structurescited by 22
- 2020Real-World Anomaly Detection by using Digital Twin Systems and Weakly-Supervised Learningcited by 17
- 2020Digital Twins: State of the Art Theory and Practice, Challenges, and Open Research Questionscited by 16
- 2021Learning Asynchronous and Sparse Human-Object Interaction in Videoscited by 16
- 2019Blockchain for Internet of Things: A Surveycited by 15
- 2015Analysis and Control of Epidemics: A survey of spreading processes on complex networkscited by 14
- 2018Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processingcited by 13
- 2021Trans4E: Link Prediction on Scholarly Knowledge Graphscited by 13
- 2018Cumulative effects of triadic closure and homophily in social networkscited by 10
- 2014Predicting commuter flows in spatial networks using a radiation model based on temporal rangescited by 9
- 2015EdgeCentric: Anomaly Detection in Edge-Attributed Networkscited by 9
- 2020Data-Driven Control of Complex Networkscited by 9
- 2016Evaluating Link Prediction Accuracy on Dynamic Networks with Added and Removed Edgescited by 8
- 2021Mutually exciting point process graphs for modelling dynamic networkscited by 8
- 2019Predicting Network Controllability Robustness: A Convolutional Neural Network Approachcited by 7
- 2020Knowledge Discovery in Cryptocurrency Transactions: A Surveycited by 7
- 2016Stochastic Multidimensional Scalingcited by 6
- 2020Big Networks: A Surveycited by 6
- 2014Probing the topological properties of complex networks modeling short written textscited by 5
- 2019Towards Optimal Robustness of Network Controllability: An Empirical Necessary Conditioncited by 5
- 2020Measuring Quadrangle Formation in Complex Networkscited by 5
- 2021Graph Based Link Prediction between Human Phenotypes and Genescited by 5
- 2013Exact Controllability of Complex Networkscited by 4
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Citing papers per year: 2022: 1; 2023: 3; 2024: 3; 2025: 1.
8 papers.
- 2023Digital Twin-Oriented Complex Networked Systems based on Heterogeneous Node Features and Interaction Rulescited by 4
- 2025Bridging the Reality Gap in Digital Twins with Context-Aware, Physics-Guided Deep Learningcited by 2
- 2023Heterogeneous Feature Representation for Digital Twin-Oriented Complex Networked Systemscited by 1
- 2023Digital Twin-Native AI-Driven Service Architecture for Industrial Networkscited by 1
- 2022From Cubes to Networks: Fast Generic Model for Synthetic Networks Generationcited by 0
- 2024AI in Energy Digital Twining: A Reinforcement Learning-based Adaptive Digital Twin Model for Green Citiescited by 0
- 2024The Role and Applications of Airport Digital Twin in Cyberattack Protection during the Generative AI Eracited by 0
- 2024Deep Reinforcement Learning for Digital Twin-Oriented Complex Networked Systemscited by 0
- 2025Bridging the Reality Gap in Digital Twins with Context-Aware, Physics-Guided Deep Learning17 May 2025
- 2024Deep Reinforcement Learning for Digital Twin-Oriented Complex Networked Systems9 Nov 2024
- 2024The Role and Applications of Airport Digital Twin in Cyberattack Protection during the Generative AI Era8 Aug 2024
- 2024AI in Energy Digital Twining: A Reinforcement Learning-based Adaptive Digital Twin Model for Green Cities28 Jan 2024
- 2023Digital Twin-Native AI-Driven Service Architecture for Industrial Networks24 Nov 2023
- 2023Heterogeneous Feature Representation for Digital Twin-Oriented Complex Networked Systems23 Sep 2023
- 2023Digital Twin-Oriented Complex Networked Systems based on Heterogeneous Node Features and Interaction Rules18 Aug 2023
- 2022From Cubes to Networks: Fast Generic Model for Synthetic Networks Generation5 Nov 2022