Fast randomized algorithm for hierarchical clustering in Vehicular Ad-Hoc Networks

Vehicular Ad-Hoc Networks (VANETs) offer communication between vehicles and infrastructure. Warning messages, among others, can be used to alert drivers, and thus improve road safety. To adapt to the unique nature of VANETs, which demands the delivery of time sensitive messages to nearby vehicles, fast topology control and scheduling algorithms are required. A clustering approach, which was initially offered for Mobile Ad-Hoc Networks (MANETs), can be adapted to VANETs to solve this problem. In this paper we present Hierarchical Clustering Algorithm (HCA), a fast randomized clustering and scheduling algorithm. HCA creates hierarchical clusters with a diameter of at most four hops. Additionally, the algorithm handles channel access and schedules transmissions within the cluster to ensure reliable communication. Unlike other clustering algorithms for VANETs, HCA does not rely on localization systems which contributes to its robustness. The running time of the algorithm was analyzed analytically and HCA was evaluated by simulation. We compared our algorithm with 2-ConID, a clustering algorithm for MANETs, under several mobility scenarios. The simulation results confirm that the algorithm behaves well under realistic vehicle mobility patterns and outperforms 2-ConID in terms of cluster stability.