Clustering Routing Protocol for Dynamic UASN Based on Voronoi Dynamic Clustering and Multi-Index Cluster Head Selection

Abstract

Underwater Acoustic Sensor Network (UASN) faces significant challenges in dynamic environments, including frequent topology changes, high propagation delay, and limited node energy, which collectively shorten network lifetime and degrade performance. This paper proposes a clustering routing protocol for dynamic UASN based on Voronoi dynamic clustering and multi-index cluster head selection, named CRDVM. This paper constructs a 3D dynamic underwater acoustic network model, and a multi-index cluster head node (CH) selection scheme is designed, which comprehensively considers the residual energy, connectivity, hop-count, and distance to the sink node, and then dynamically selects CHs through a fuzzy inference system. Then, the intra-cluster routing employs a distance weighted minimum spanning tree (MST) to shorten transmission paths, whereas inter-cluster routing uses an MST weighted by dual metrics to balance CH energy consumption while low delay. Voronoi graph theory is introduced to realize adaptive clustering in a dynamic environment. Simulation results demonstrate that, compared with QD-DCR, UCPSO, LCOA-ASPPM, and CCCS, the proposed CRDVM achieves a longer network lifetime and better energy balance while keeping delay low.