Clustering Problem in Self-Organising Communication Networks on the Example of Smart Vehicle Transportation System
Summary
Efficient communication in many types of dynamic networks depends critically on how nodes are clustered into subnetworks. As such networks grow and evolve rapidly, there is a need for fast and robust clustering algorithms that account for communication cost structures induced by different node partitions. In this paper, we evaluate how classic community detection algorithms (CDAs), i.e. the Louvain and Ensemble Clustering for Graphs (ECG), adapted to incorporate a flexible family of cost functions, perform relative to standard heuristic and metaheuristic approaches.
Using simulations on l-nearest neighbour graphs of varying sizes, we find that especially the Louvain algorithm consistently delivers high quality solutions at a substantially lower computational cost.
In contrast, metaheuristic methods fail to scale effectively, and the ECG algorithm does not provide performance improvements in our setting, despite its reported stabilising effect in traditional community detection tasks.
Overall, our results indicate that classic CDAs are well suited for real time clustering in dynamic communication networks and constitute a strong basis for developing scalable communication optimisation strategies.
Keywords
Transport Networks, Communication Networks, Network Design, Graph Clustering
Journal Impact Factor: N/A
Publication date: March 2026
Links
References
| APA | Antosiewicz, M., Szufel, P., Kami艅ski, B., Skorupka, A. Pra艂at, P., & Mashatan, A. (2025). Clustering problem in self-organising communication networks on the example of smart vehicle transportation system. Przegl膮d Statystyczny. Statistical Review, 72(4), 1鈥�24. |
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| BibTeX | @article{antosiewicz2025clustering, title={Clustering problem in self-organising communication networks on the example of smart vehicle transportation system.}, author={Antosiewicz, Marek and Szufel,聽Przemys{\l}aw and Kami{\'n}ski, Bogumi{\l} and Skorupka, Agata and Pra{\l}at, Pawe{\l} and Mashatan, Atefeh}, journal={Statistical Review/Przegl{\k{a}}d Statystyczny}, year={2025} } |
| DOI | https://doi.org/10.59139/ps.2025.04.1 |
| IEEE | M. Antosiewicz, P. Szufel, B. Kami艅ski, A. Skorupka, P. Pra艂at, and A. Mashatan, 鈥淐lustering problem in self-organising communication networks on the example of smart vehicle transportation system,鈥� Przegl膮d Statystyczny Statistical Review, vol. 2025, no. 4, pp. 1鈥�24, Mar. 2026. |
| ISSN | 0033-2372 |
Acknowledgement
This research was funded in part through a generous contribution from as well as the grants from and .