Improved particle swarm optimization algorithm of clustering in underwater acoustic sensor networks

Aiming at improving the poor stability and unsatisfactory clustering results of the existing underwater acoustic sensor networks (UASNs) clustering algorithms, this paper proposes a new clustering model. In the model the required transmission power of sensor nodes, as well as the cluster head residual energy and the cluster head loads are among consideration. With the clustering model, we design a novel clustering algorithm based on the discrete particle swarm optimization algorithm (PSO). We use the proposed clustering algorithm to cluster UASNs periodically with the cluster head being rotated dynamically. Simulation results demonstrate the reduction in network energy consumption and the prolonged network lifetime. Moreover it achieves higher stability.