CLEVeR: Enhancing Cluster Leader Election in Ad Hoc Networks

• Vinicius B. Jesus UFBA
• Lucas M. Almeida UFBA
• Weslei F. Santos UFBA
• Joahannes B. D. da Costa UNIFESP
• Geraldo P. Rocha Filho UESB
• Maycon L. M. Peixoto UFBA

DOI: https://doi.org/10.5753/sbrc.2026.19751

Abstract

Vehicular Ad Hoc Networks (VANETs) require efficient leader election mechanisms to mitigate communication overhead in highly dynamic environments. Existing strategies typically rely on topological centrality metrics while overlooking mobility stability, which can result in leaders that quickly lose representativeness. This paper presents CLEVeR, a cluster-based predictive leader election model that integrates connectivity and vehicular mobility using a Gradient Boosting Regressor to estimate a leadership score. By replacing purely metric-based selection with supervised inference, the approach produces more stable and representative leaders without introducing significant computational overhead. Simulations conducted in realistic urban scenarios demonstrate that CLEVeR achieves higher leadership scores and reduces mobility instability by more than 40% compared to Betweennessand Closeness-based methods, while also exhibiting lower variability across executions.

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