An energy-efficient multi-level adaptive clustering routing algorithm for underwater wireless sensor networks

Excessive energy loss is caused by premature node death and lower energy utilization efficiency in underwater acoustic sensor networks. Network-based clustering methods can use a cluster head to fuse data within the cluster members for forwarding, instead of each node forwarding data alone, which can effectively reduce the total energy loss in the process of transmission. Therefore, an energy-efficient adaptive clustering routing algorithm for underwater acoustic sensor network is proposed (ACUN). The algorithm uses a multi-level hierarchical network structure based on the distance between cluster heads and the sink node and the residual energy of a cluster head to determine the size of the competition radius. It can avoid early death of a cluster head away from the sink node because of excessive competition radius leading to excessive energy burdens. When selecting a cluster head, considering node residual energy and the energy loss of a transmission path, the algorithm can select a node with larger residual energy as a cluster head while optimizing network energy consumption. Routing rules are adopted according to the residual energy conditions of the nodes to choose a more energy-efficient single-hop routing node or multi-hop routing in favor of energy balance. Simulation experiments show that the ACUN algorithm compared with the AFP protocol and DEBCR algorithm results in more energy savings and an extended working life of network nodes.