## 2 Literature Review  
The authors investigated various parameters that have an impact on energy-efficient routing in UWSNs. We analyze the factors that influence the selection of optimal routing paths in order to minimize energy consumption and prolong the network lifetime. The examined parameters include node density, transmission range, routing protocols, and energy-aware algorithms. By understanding these key elements, we can develop effective strategies to enhance the energy efficiency of UWSNs, leading to improved network performance and extended operational duration nodes for the connection. The relay node transmits the packet as quickly as possible to the destination node, which accepts and acknowledges the packet. To receive or rebroadcast packets efficiently, time-reliable scheduling must be established between the relay, source, and destination nodes [15]. This resolves the issue of packet loss. According to simulation case studies, the proposed approach outperforms some existing schemes in terms of packet delivery to the destination [16] A micro-ANP protocol architecture was devised for UAN. It consists of three layers: application, network transport, and physical. In addition, this paper provides a comprehensive description of a handshake-free consistent communication method based on the micro-ANP design and recursive LT encoding. Diverse structures of hydroacoustic communication networks are investigated in [17; 18; 19; 20], considering their potential for UWSN consumption reduction. Multipath fading, rapid fading of acoustic signals, and extended propagation delays are characteristics of these structures. The absolute selection of forwarding nodes frequently results in node demise, resulting in unequal energy conservation and network vacancies. The objective of their model, which is known as the geographic opportunity routing model, is to reduce energy tolerance deficits and imbalances. It is a mobile-assisted model that prevents UWSN interference. Among other advantages, the network volume is divided into small logical units to minimize interference and provide a more informed routing consideration for energy-efficient protocol consumption. The authors of [21] suggested assigning an optimal number of transponder nodes to each cube based on its proximity to the destination to prevent invalid events within the cubes. In addition, removable receivers are used to improve packets from the vacant section, thereby reducing data traffic on intermediate nodes. To validate their proposed work, extensive simulations were conducted with a focus on exploiting and maximizing the network's lifecycle and packet delivery rate. According to the authors, the problem of determining the AUV's route must be addressed in order to enhance the value of information (VoI) of the actual data transmitted to the sea sink node. They proposed an adaptive and greedy AUV routing algorithm that directs AUVs to collect data from nodes whose proper operation depends on Vol and their data. The authors presented a framework for integer linear programming that precisely models the estimated setup to generate a route for the AUV to collect and transmit more VoI data. This allowed them to evaluate the effectiveness of the AUV's routing strategy. Experiments revealed that greedy adaptive AUV path planning (GAAP) consistently provided more than 81% of the optimal centralized VoI solution based on the integer linear programming (ILP) model. The cases examined led to the development of a route that enabled the autonomous underwater vehicle (AUV) to be deployed for data collection. AUVs collect and transmit data with an extraordinarily high V-o-I while adhering to operational constraints. They compared the efficacy of GAAP and other methods for transferring AUVs between sensing nodes, including random routes, traveling salesman problem (TSP)-based routes, and \"lawnmower\" patterns.