The Underwater Acoustic Sensor Networks has drawn the attention of researchers around the globe because of its diversified applications. The network is based on battery-operated acoustic sensor nodes therefore, it is of utmost significance to design energy efficient routing protocol. One of the major reasons for inefficient energy consumption is the imbalance utilization of energy in different areas of the underwater region which leads to hotspot issues. In this article, a novel localization-free Energy Efficient Clustering Routing Protocol based on Arithmetic Progression (EECRAP) is proposed. The underwater region logically segmented into asymmetric layers based on Arithmetic Progression. The proposed solution is based on the residual energy, layer division, and depth division of the node which can mitigate the hotspot issue and balance energy utilization in the network. For energy preservation and network longevity, an innovative energy-efficient routing path selection is presented in which the succeeding forwarder node is selected according to its residual energy, layer division, and the received signal strength. When compared with Low-Energy Adaptive Clustering Hierarchy (LEACH), Depth Based Routing (DBR), Energy Efficient Routing Protocol Based on Layers and unequal Clusters (EERBLC), and energy efficient clustering multi-hop routing protocol (EECMR), the simulated results illustrate improvements in energy usage of 40.7%, 29%, 20.25%, and 11% over LEACH, EERBLC, DBR, and EECMR respectively. Packet Delivery Ratio-wise, EECRAP is 58.44%, 55.77%, 49.87%, and 7.61% dependable than DBR, LEACH, EERBLC, and EECMR respectively. Dead nodes make EECRAP 68.7%, 23.1%, 8.7%, and 7.6% more efficient than LEACH, DBR, EERBLC, and EECMR respectively.

Underwater Acoustic Sensor Network (UASN) is a rapidly growing technology and a buzzword among recent researchers due to unreached, hidden, and desirable underwater resources. Like other technologies, UASN also has some challenges which include low propagation delay, free-floating underwater sensor nodes, low bandwidth, and reliability of data delivery. Among all these challenges, efficient utilization of energy from sensor nodes during data transmission and prolongation of network lifetime is the topmost challenge. Several researchers have made substantial contributions to address it by designing energy efficient routing protocols. This research paper focuses on presenting some of the significant work performed in this area. In this research paper, some of the recently developed cluster-based routing protocols are reviewed. A critical review approach is adopted to see existing routing protocols strengths and weaknesses and focus on the issues. The performance factors which are considered and ignored, reviewed in this research paper. In the end, some open areas are discussed for potential research work. This research paper is helpful for the researchers from academic circles and industries who are new in this research field and want to contribute by designing energy efficient clustered based routing protocol to mitigate excessive power consumption by Underwater Acoustic Sensor Networks.

The Underwater Acoustic Sensor Networks have gained significant attention because of their wide range of applications in submerged environments. However, ensuring reliable and energy-efficient communication in the submerged environment is challenging due to their distinctive characteristics such as limited energy resources, dynamic topology, extended propagation delays, and node mobility. Additionally, the void hole problem in submerged environments arises due to randomized node deployment. To curtail these issues, this paper introduces a novel way of strategically deploying the nodes based on the underwater depth parameters, which can reduce the likelihood of void hole occurrence. An optimal number of clusters based on the fixed transmission range of cluster heads is used to cater to extensive energy usage. In the proposed routing protocol, the path selection is based on the residual energy, link quality, and proximity to a higher number of nodes. Extensive simulations have been conducted by varying network parameters to analyze the network performance in terms of energy expenditure, packet delivery ratio, network throughput, number of dead nodes, and end-to-end delays. Also, the proposed work provides a performance comparison with some state-of-the-art protocols and exhibits promising results.

Due to unexplored but desirable undersea resources, Underwater Sensor Network, is developing technology and becomes a catchword for modern scientists. Underwater Acoustic Sensor Networks, also known as UASN, are employed for a broad range of underwater utilizations such as reconnaissance by the military, mineral ore detection, oil reservoir management, aquatic environment exploration, imaging marine life, and early warnings to prevent a natural disaster. Almost every application is triggering to monitor important characteristics such as the salinity concerning different levels of depth, temperature profile, pollutants, etc. However, the study of aquatic channel characteristics is required before implementing the UASN for any of the applications. This research paper presents the underwater channel characteristics by varying the acoustic signal frequency, underwater depth levels, and separation between nodes. The simulated result is generated using MATLAB. The findings in the form of graphical representations are satisfactory and may be considered for future research in UASN.

Underwater Acoustic Sensor Networks (UASNs) play a critical role in underwater exploration, yet face challenges like high energy consumption, and uneven load distribution in multi-hop routing. While existing clustering protocols like Anchor Nodes assisted Cluster-based Routing Protocol (ANCRP) have improved energy-efficiency through uniform cluster formation, they still suffer from unequal energy depletion among cluster heads (CHs), particularly in shallower layers. This paper introduces key innovations that advance cluster-based routing in UASNs. We propose an Energy-Adaptive Non-uniform Clustering Protocol (EANCP) with three novel aspects: (1) depth-optimized cluster sizing where deeper CHs manage larger clusters with lower communication demands while shallower CHs handle smaller clusters to prevent early energy depletion; (2) an adaptive beaconing mechanism where transmission rate varies with depth to conserve energy in stable deep regions; and (3) a multi-criteria CH selection strategy considering residual energy, congestion, and distance to sink. The protocol was designed and simulated in Python, leveraging its scientific computing ecosystem (NumPy, SciPy, and Matplotlib) for flexible modeling of underwater acoustic channels and energy consumption. Unlike ANCRP’s uniform approach, EANCP’s depth-aware design addresses the uneven energy consumption in UASNs. Simulations demonstrate significant improvements: a 14% lower energy consumption, 11.5% longer network lifetime, 5−8% higher packet delivery ratio (PDR) and 20% lower delays compared to ANCRP. The protocol particularly excels in large-scale deployment by preventing routing bottlenecks through congestion-aware forwarding. These advancements make EANCP a significant improvement in underwater routing protocols, offering a more robust solution to balancing energy efficiency with reliable communication in harsh underwater environments.