# Hybrid Dual-Link Data Transmission Based on Internet of Vessels
## 2 Related Work  
To improve the reliability of data collection in underwater environments, recent years have seen significant research into the use of Underwater Sensor Networks (UWSNs) for underwater data transmission. The findings in this area are highly relevant to this paper. Underwater Sensor Networks are an essential component of marine networks, wherein sensor nodes are deployed underwater, and communication links are established to enable the real-time monitoring, data collection, and information transmission of the marine environment [5; 6]. However, unlike electromagnetic wave transmission on land, acoustic waves in water propagate more slowly and are influenced by phenomena such as multipath propagation, reflection, and diffraction. The path loss in underwater transmission is substantial, with severe signal attenuation and limited transmission distance [7]. Therefore, designing an effective mechanism that allows UWSNs to achieve long-distance, large-volume data collection and transmission under acoustic transmission conditions poses a significant challenge. Given the inherent limitations of UWSNs, current research methods in the literature can be categorized into two approaches: one is using multi-hop routing for data transmission, and the other is deploying flexible Autonomous Underwater Vehicles (AUVs) and Unmanned Underwater Vehicles (UUVs) to assist with data collection and transmission. In AUV-assisted transmission schemes, network models are generally divided into three categories [8]: (I) Distributed Networks [9; 10; 11]: nodes are independently distributed, and AUVs need to access each node, although this is less efficient. (II) Node grouping based on fixed AUV paths [12; 13]: limited by the fixed AUV path and network architecture, the primary goal is to avoid conflicts between nodes and increase network throughput, but the fixed AUV path restricts the network's flexibility. (III) AUV-assisted clustering networks [14]: network nodes are divided into clusters, and AUVs only collect data from cluster heads, significantly reducing the AUV travel time. By properly selecting cluster heads and carefully designing clustering algorithms, network performance can be significantly improved. In multi-hop transmission methods, most UWSN data transmission approaches focus on energy consumption. Existing energy-efficient routing algorithms for UWSNs can be classified into three categories: depth-based routing algorithms [15; 16], clustering-based routing algorithms [17; 18; 19], and cooperative reliability-based routing algorithms [20; 21]. These algorithms aim to reduce energy consumption and delay node failure times. However, due to issues like network voids and the limitations of the algorithms themselves, even with sufficient live nodes in the UWSN, the network may still fail prematurely if an important node encounters problems and data cannot be transmitted effectively. To address the energy consumption of aggregation nodes in long-distance data transmission, methods using drone-assisted aggregation nodes for data transmission have been proposed [22]. Drone data collection offers higher flexibility, with lower deployment and transmission latency, and higher bandwidth, among other advantages, but requires reliable drone deployment or path planning algorithms [23]. To achieve collaborative communication and resource sharing in storage, a maritime data transmission scheme assisted by unmanned surface vehicles (USVs) has been proposed [24]. We summarize the comparison of the advantages and disadvantages of HDTA and other related references in certain aspects in Table 1.The checkmark indicates that the specific study in the reference demonstrates significant advantages in certain aspects compared to other studies. However, most of the aforementioned studies still face significant challenges posed by the inherent limitations of underwater communications, such as severe path loss, limited transmission range, high signal attenuation, and problems related to multipath propagation and environmental interference.