## 1 Introduction  
The high-paced emergence of communication technologies and associated applications has gained significant attention across academia and industry to enable efficient low cost, energy efficient and quality of service (QoS) communication support. In the last few decades, providing underwater communication has emerged as a vital research domain for both academicians as well as industries. Recently, underwater wireless sensor networks (UWSNs) [1, 2] have been used exponentially in varied applications including environmental monitoring, gas deposit exploration, tsunami warning, assisted navigation, distributed tactical surveillance, mine reconnaissance, oceanographic data collection, oil spill monitoring, real-time warship monitoring, disaster prevention, etc. Although UWSN is stated to be closely related to the WSN, many research reports [3, 4, 5, 6] have revealed that generic techniques developed for WSNs cannot be applied for UWSNs, due to the practical operating characteristics of the underwater channel [7]. The main issues allied with the underwater channel comprise high propagation latency caused by low propagation speed of acoustic signals (usually, 1500 m/s), strictly confined accessible resources [8], wave caused disturbance, noise presence, dynamic delays [9] and high error rate probability. The dynamic topological variations also make protocols vulnerable to suffering link loss and data drop across multipath and fading channel conditions [10]. This might cause significantly higher data retransmissions, increased latency, high energy exhaustion and cumulative QoS degradation. To alleviate such issues, enabling an efficient routing protocol while ensuring optimal data delivery, throughput and minimal energy exhaustion can be of paramount significance. Exploring this issue in-depth, it can be found that most existing physical layer approaches are ineffective [11]. In fact, radio waves propagating across conductive salty water at a low-frequency range (i.e., 30-300 Hz) require significantly large antennae and, as a result, more transmission power. Undoubtedly, optical waves avoid major attenuation issues, however, they are influenced by scattering under water surface. This problem demands an efficient UWSN routing protocol to deal with different acoustic environment conditions. Considering the functional characteristics and associated intricacies, it is necessary to assign sufficient resources before system deployment to enable optimal QoS transmission on both the PHY link layer as well as the higher network layers. Providing an efficient channel model to consider realistic network conditions can enable development of an optimal routing approach. In major existing approaches, numerous beam tracing tools, such as Bellhop [11], have been suggested for the deterministic presentation of a UWA channel for certain predefined signal features, such as frequency and network geometry. However, this does not consider the arbitrary nature of channel conditions. To deal with these conditions, statistical channel models have gained appreciation, for example, the Virtual Times series EXperiment (VirTEX) code [12] based channel model, which outperforms the Bellhop model due to its beam tracing efficiency under dynamic channel conditions. However, its computational efficiency remains questionable. For illustration, to simulate a channel with a Doppler distortion of 15 Hz, a minimum of 30 channel simulations per second are needed, which eventually piles up iterations to a significantly higher 5400 Bellhop runs, even with two transmitters and six receivers over a period of 15 s. Similarly, the wave front model [13] provides a deterministic approach to enable approximations to the ray theory. The authors of [14] assessed the impact of warping of the oceanic surface waves on the fluctuations introduced, particularly in terms of transmission latency and throughput.