Multi-AUV Collaborative Data Collection Scheme to Clustering and Routing for Heterogeneous UWSNs

A collaborative data collection scheme with autonomous underwater vehicles (AUVs) based on multiobjective optimization is proposed for the heterogeneous underwater sensor networks. Recognizing the interconnectedness between clustering and path planning, addressing them separately results in unbalanced clusters and paths, limiting performance optimization. To address the above issues, this article considers clustering and AUV path planning as a whole and designs an integrated cluster and path planner (ICPP) to optimize network performance jointly. At the same time, in order to reduce data collection delay, multiple AUVs are used to collaborate in data collection. This article sets appropriate objective functions and chromosome encoding to obtain visiting paths for multiple AUVs simultaneously. In the heterogeneous underwater wireless sensor networks (UWSNs), in order to extend the lifetime of UWSNs, we consider the energy level and location of sensor nodes when selecting the cluster head (CH). Nodes with more residual energy and more dispersed nodes are more likely to be selected as the CH. Through experimental simulation verification, we demonstrate the performance advantages of the ICPP, indicating that better balance and efficiency have been achieved in the data collection scheme of heterogeneous UWSNs.