AUV-aided isolated sub-network prevention for reliable data collection by underwater wireless sensor networks

Abstract

The unique characteristics of the underwater environment, such as limited infrastructure, challenging acoustic communication channels, and constrained battery power of underwater sensor nodes, significantly impact the overall network lifetime of underwater wireless sensor networks (UWSNs). In a multi-hop UWSN, the death of a special node — cut-vertex (CV) — divides the network into the main network and an isolated sub-network (ISN). The UWSN may struggle to operate continuously and efficiently owing to the death of underwater sensor nodes, resulting in a shorter network lifetime and reduced data reliability. Consequently, the data generated by the ISN is lost. To address this issue, this paper presents an autonomous underwater vehicle (AUV)-aided ISN prevention protocol for UWSNs. The proposed protocol employs an AUV to explore and identify a CV by utilizing the information collected from the sensor nodes. Subsequently, the AUV predicts the future residual energy of the CV, ensuring its arrival near the CV prior to the energy depletion of the CV and the formation of an ISN. Then, instead of the CV, the AUV directly collects data from the CV-associated sensor nodes while the CV harvests energy. The CV replenishes its energy by harnessing ambient underwater sources and subsequently reintegrates into the network after attaining sufficient energy recharge. In this study, we evaluate the performance of the proposed protocol by comparing it with the Q-learning-based topology-aware routing protocol, a hybrid data-collection scheme, stratification-based data-collection scheme, and Q-learning-based energy-efficient and lifetime-aware routing protocol in terms of the lifetime of the network, lifetime of the CVs, energy consumption, end-to-end delay, and packet delivery ratio.