## 3 Related Studies  
[PERSON] et al. modified the well-known ALOHA (Medium Access Convention) model in 2019. Thus, channel utilization might be enhanced. The new model features an enhanced ALOHA-Q (UW-ALOHA-Q). Unusual activity, a reduction in the number of openings per outline, and a unified arbitrary conspiracy are suggested to improve the UW-ALOHA-Q. The suggested methodology comprehensively improves utilization regarding the number of openings per outline while providing yet another arbitrary back-off mechanism to achieve impact-free planning. For subsea systems with a range of 1000 m, UW-ALOHA-Q boosted channel usability by up to 24.6 times [16]. [PERSON] et al. provided a study of the UWSN's multiple borders and an overview of the network. They also examined a few additional categories, including MAC, routing protocols, natural elements, restriction, and channel associations. They also clarified the nonlinear sound growth of acoustic indicators. The media and directing receive organized control measures when dealing with rising channel utilization [17]. A detailed analysis of UWSN routing algorithms by [PERSON] and [PERSON] was released in 2019. Using this framework, they assessed the proposed solutions in light of the routing protocol's core principles. \"Localization-based\" and \"Localization-free\" routes are two different router protocols. There are several issues in designing routing protocols that consider issues like energy constraints and void avoidance requirements, as well as recognizing position, mobility, and 3D deployment. As more guiding tactics use the versatility offered by such conditions, the prevalence of underwater acoustic sensor systems is growing. Their main concern was maximizing network performance through energy balance [18]. [PERSON] et al., in 2019, created a cluster-based energy-efficient UWSN that can reduce energy costs and increase effectiveness in underwater situations. The supplied cluster-based underwater wireless sensor network (CUWSN) is designed with a UWSN architecture that benefits from CH and multi-hop transmission. As mentioned above, the multi-hop transmissions of the CUWSN extend the network's lifetime [19]. [PERSON] et al., who surveyed the current best-in-class underwater problems, audited the UWSNs. It was discovered that the study's main focus was on the currently used undersea limitation techniques. There is much interest among researchers aimed at lifting undersea constraints on the UWSN. As a result of their study, several faults in the current  
Figure 3: Submerged sensor’s internal structure. procedures were fixed. \"Evaluated\" and \"forecast-based\" classifications are additional subcategories. Different underwater limitation techniques are explored and compared based on their feasibility [20]. For data transmission in the Underwater Acoustic Sensor Network, [PERSON] et al. used [PERSON]'s Lion Optimized Cognitive Acoustic Network (LOCAN) algorithm to handle packet deferral and bundle misfortune (UWASN). The proposed model uses Doppler impact and geometric spreading techniques (GS). Currently, salinity and temperature are the only variables being taken into account. The main driving forces behind the first method are the movement of the sensor hub and changes in the ocean's surface. Because of the profundity, the waves' wavefront areas change around the hub, and the second technique is utilized. The amount of sound dispersion influences bundle transmission. A multifaceted strategy is used to construct the suggested procedure. By fitting a channel choice based on the variety of water segments, the LOCAN technique outperforms COCAN, by a significant margin, in enhancing the hub's productivity and battery life under Doppler and geometric spreading (GS) conditions [21]. A low-energy adaptive clustering hierarchy (LEACH) approach was used by [PERSON] et al. to reduce this node's power consumption and lengthen its network life. The network areas are separated into layers based on the depth levels.