Beetle colony optimization algorithm-based node clustering scheme for efficient data dissemination in vehicular ad hoc networks

Vehicular ad hoc networks (VANETs) are the ultimate solution for preventing road accidents, which result in the loss of precious human life worldwide. In this context, effective communication between the vehicular nodes is essential due to the varying network topology and high vehicular mobility inherent with VANETs. Cluster-based routing is identified to be a significant approach for achieving efficient routing and improving communication proficiency in VANETs. In this paper, a beetle colony optimization algorithm–based clustering scheme (BCOACS) is proposed for generating optimized clusters for facilitating reliable data dissemination. This BCOACS algorithm includes two vital strategies such as beetle antenna search (BAS) and swarm intelligence for attaining inter-cluster and intra-cluster communications. In specific, BAS strategy that includes random search attributed toward gradient direction is used for intra-cluster communication without using the complete amount of gradient information. On the other hand, a swarm intelligence strategy that encompasses a collective approach of self-organized and decentralized agents is used for inter-cluster communication with the view to minimize the load on each cluster head (CH) and to extend the clusters' lifetime. The simulation outcomes of the proposed BCOACS scheme confirmed improved performance in optimizing the number of constructed clusters independent of the increase in the network grid size, transmission range, and number of vehicular nodes in the network compared to the benchmarked approaches. The results also confirmed that the proposed BCOACS scheme achieved a maximized throughput of 13.42%, with reduced delay and protocol overhead of 18.96% and 19.45%, better than the benchmarked schemes used for investigation.