## 1 Introduction  
About 70% of the Earth's surface is water, spanning oceans, seas, rivers, and lakes [1, 2]. This vast region likely conceals valued resources, like cobalt, copper, nickel, silver, and gold, yet their exploration remains challenging due to hazardous submerge conditions. Despite their immense importance, around 94% of ocean resources remain untapped [1]. Technological advancements allow for the placement of sensor nodes in river ecosystems, lakes and natural forestry for research purposes. Sensor nodes used in underwater environments can be grouped to form an Underwater Wireless Sensor Network (UWSN) to measure environmental conditions at different depths in bodies of water like seas, oceans, rivers, and lakes. Their uses also include seismic tracking [3], underwater mine detection [4], submarine tracking [5], and monitoring oil and gas pipelines [6]. Due to the peculiar nature of submerged environment, underwater communication differs from terrestrial communication [7, 8]. Terrestrial Wireless Sensor Networks operate using radio signals. However, radio signals experience poor propagation and attenuation in underwater conditions, while acoustic signals offer superior wireless communication due to greater range, less attenuation, and increased reliability [9]. Hence, UWSN technologies are used underwater with sensors that utilize acoustic waves for communication, which are known as Underwater Acoustic Sensor Networks (UASNs). The general architecture of a UASN is shown in Figure 1.  
The UASN nodes primarily rely on batteries that are challenging to replace, posing difficulties in recharging the sensor nodes [10; 11]. Considering the issue, many different routing techniques are suggested to improve energy-efficient usage by utilizing direct or multi-hop data transfer schemes with optimal energy usage. However, cluster-based routing algorithms are generally preferred in UASNs due to their adequate energy conservation performance [12; 13; 14; 15; 16]. During cluster-based routing, a cluster is formed by multiple neighboring nodes, and a cluster head is chosen among the sensor nodes using an election mechanism. Once the sensor readings are collected in individual clusters, the cluster heads efficiently transmit the data using nearby cluster heads through multi-hop routing [17]. However, repetitive data transfer depletes the energy of intermediary nodes over time, leading to a lower lifespan compared to other nodes and causing connection failure [6]. The bridges' failure causes a disconnect between the cluster heads and sinks, which is known as the void-hole issue in UASNs. The void issue illustration can be seen in Figure 2. This issue significantly decreases the network's lifespan. As a result, many data-forwarding strategies have been proposed for UASN data routing to reduce this unequal energy usage as well as address network void issues [18; 19; 20; 21]. Void regions in UASNs commonly occur due to [9; 22; 23] (a) sparsely deployed sensor nodes in a network because of their high cost; (b) sensor nodes failing because of premature demise, corrosion, or fouling; (c) the displacement of sensor nodes because of water current; (d) obstructed communication between sensor nodes because of ships or underwater animals; (e) acoustic channel properties affecting because of the variation in the signal strength. However, void regions typically result from the sparse distribution of expensive underwater sensor nodes with restricted transmission range [22]. Therefore, deploying an excessive number of underwater acoustic sensor nodes to cover the underwater monitoring region may not be feasible due to the high price of these nodes. These void regions create detachments in the submerged network, which leads to decreased network connectivity and an increased packet drop ratio. Eventually for successful packet reception at the sink node, multiple retransmissions of similar packets are needed, which require higher energy.