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Green Vehicular Ad-hoc Network (VANET) is a newly-emerged research area whichfocuses on reducing harmful impacts of vehicular communication equipments onthe natural environment. Recent studies have shown that grouping vehicles intoclusters for green communications in VANETs can significantly improvenetworking efficiency and reduce infrastructure costs. As a dynamic networksystem, maintaining the network connectivity and reducing the communicationoverlap are two critical challenges for green VANET clustering. However, mostexisting work studies connectivity and overlap separately, lacking a deepunderstanding of the relationship between them. To address this issue, wepresent a comprehensive analysis that jointly considers the two criticalfactors in one model. Specifically, we first design a state resemblanceprediction (SRP) model based on the historical trajectory feature relevancebetween vehicles; Combined with the SRP model, we propose the region-basedcollaborative management scheme (RCMS) to establish the dynamic clustering;Lastly, we take extensive experiments to verify the region-based collaborativemanagement scheme for dynamic clustering. The results demonstrate that theproposed clustering algorithm can achieve high networking efficiency and bettercommunication stability.

A Region-based Collaborative Management Scheme for Dynamic Clustering in Green VANET