Fuzzy C-Means Clustering and Improved Arithmetic Optimization Algorithm-Based Layering Cooperative Routing Protocol for UASNs

In underwater acoustic sensor networks (UASNs), the energy resources available to the underwater nodes are severely limited. The depletion of node energy can decrease network connectivity and shorten the lifetime of the network. Clustering routing has been proven to be an effective technique for improving energy efficiency and extending the lifetime of the network. Therefore, concerning the problems of nonuniform clustering, unbalanced energy consumption, and short network lifetime in existing cluster routing protocols, a fuzzy C-means clustering and improved arithmetic optimization algorithm-based layering cooperative routing (FCALCR) protocol for 3-D static UASNs is proposed in this article. The FCALCR protocol introduces a fuzzy C-mean (FCM) algorithm to cluster the nodes in the network, which achieves uniform clustering. Each node is configured a layer to facilitate data packets to be transmitted layer by layer to the sink, which improves the reliability of the packet transmission. Furthermore, a Sobol sequence and multistage dynamic perturbation strategy-based arithmetic optimization algorithm (AOA) is proposed to select the best cluster head forwarding node, which accelerates the convergence speed and improves the robustness of the routing protocol. Simulation results show that the proposed FCALCR protocol outperforms the protocols of low-energy adaptive clustering hierarchy (LEACH), LEACH-expected residual energy (ERE), energy-efficiency grid routing based on 3D cubes (EGRC), FCM and moth flame optimization method (FCMMFO), and energy-efficient clustering routing protocol (EECRP) in terms of network lifetime and packet transmission efficiency.