Integrating Environmental Awareness in Underwater Acoustic Networks: A Comprehensive Review

This paper proposes an efficient spectrum manage scheme to fulfill environment-friendly and spectrum-efficient communication for underwater cognitive acoustic networks (UCANs). Due to the frequency-dependent attenuation, the available communication frequencies in water are severely limited. Nevertheless, this precious resource is still underutilized. In this paper, the problem of multiple cognitive acoustic (CA) users sharing available channels and optimal power allocation in underwater acoustic networks are studied. It aims to provide efficient spectrum utilization for CA users while avoiding harmful interference with both natural acoustic systems, such as whale, dolphin, and artificial acoustic systems, like sonar users and other underwater acoustic networks.

Underwater Acoustic Network (UAN) is an emerging technology suitable for many marine applications ranging from marine data collection to surveillance applications. In this article, we propose an underwater acoustic communication network for multi-AUV target localization, which can also be applied in other multi-AUV collaboration tasks. The proposed UAN takes into account the characteristics of the underwater acoustic channel of the multi-AUV system and the requirements of the communication for cooperative tasks, and provides reliable and efficient underwater communication. In September 2020, a experiment about multi-AUV underwater collaboration and communication was carried out in Sanya. The network is composed of three AUVs and surface control nodes. We conducted an experiment to illustrate the special channel characteristics of the UAN of multi-AUV system, and the reliability and practicability of the proposed network are verified in the multi-AUV Cooperative target location experiment.

With the extensive application of underwater acoustic sensor networks (UANs) in various fields such as commerce, marine environmental research, and national defense, the need for an autonomous and well-organized underwater acoustic network has been increasing. Topology discovery is a crucial step in constructing an underwater acoustic network, and node discovery and topology establishment are the essential components of the topology discovery process in UANs. This paper introduces the characteristics of underwater acoustic channels and networks and highlights their influences on topology discovery. We discuss the topology discovery protocol development in terrestrial networks (i.e., duty-cycle ad hoc network, Internet of things). The main focus of this paper is to study the topology discovery protocols of UANs. This paper also classifies and introduces the existing topology discovery protocols and compared their advantages and disadvantages to understand the current topology discovery methods. Furthermore, we also discuss the topology discovery protocol’s influence on different layers’ functions in the UAN protocol stack. Analyze the current research challenges in this field, followed by important open issues in UAN protocol development, which provide new opportunities for further research.

Wireless underwater acoustic (UWA) networks serve several civilian and military applications. The multiple reflections and dispersion, along with the long propagation delay limit the sum rate of UWA networks. Earlier works discussed adding full-duplex (FD), relay assistance, and non-orthogonal multiple access (NOMA) to enhance the system sum rate. Another challenge in UWA networks is the power limitation of devices. Hence, power optimization is crucial to maximize the energy efficiency. Furthermore, securing the UWA network against eavesdropping is essential to guarantee the confidentiality of communication. This work optimizes the power to maximize the secrecy sum rate (SSR) of a FD relay-assisted NOMA (FD-R-NOMA) underwater acoustic network subjected to an eavesdropper (Eve) attack. The network is studied in two states: when the network has or not the channel information (CI) of the threat. FD-R-NOMA UWA network shows to be more resilient to eavesdropping with higher secrecy energy efficiency when compared to the conventional half-duplex orthogonal multiple access network. Also, the results reveal that knowing the CI of the Eve improves the SSR of the network. Besides, the results show the effect of factors like the location of Eve, interference cancellation efficiency, noise in the environment, and sensor distributions in the system.

In oceans, both the natural acoustic systems (such as marine mammals) and artificial acoustic systems [like underwater acoustic networks (UANs) and sonar users] use acoustic signal for communication, echolocation, sensing, and detection. This makes the channel spectrum heavily shared by various underwater acoustic systems. Nevertheless, the precious spectrum resource is still underutilized temporally and spatially in underwater environments. To efficiently utilize the spectrum while avoiding harmful interference with other acoustic systems, a smart UAN should be aware of the surrounding environment and reconfigure their operation parameters. Unfortunately, existing UAN designs have mainly focused on the single network scenario, and very few studies have considered the presence of nearby acoustic activities. In this paper, we advocate cognitive acoustic as a promising technique to develop an environment-friendly UAN with high spectrum utilization. However, underwater cognitive acoustic networks (UCANs) also pose grand challenges due to the unique features of underwater channel and acoustic systems. In this paper, we comprehensively investigate these unique characteristics and their impact on the UCAN design. Finally, possible solutions to tackle such challenges are advocated.

The highly precise time synchronization is very important to underwater acoustic (UWA) networks (UANs) and underwater targets and vehicles. It consists of a variable number of sensors and vehicles that are deployed to perform collaborative monitoring tasks over given area. The UANs are envisioned to enable applied widely for oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation and tactical surveillance applications. In the paper, the main purpose is to provide highly precise time synchronization method for the underwater objects. The general designing scheme, the theory of the underwater orientation and navigation and the method of signal processing were given. The results of the underwater experiments show that the precision of time synchronization are 10 ns, 30 ns for a 100 m (stationary) baseline and a 8 km baseline respectively. The experiments also indicate that the major influence factors are complicated for the underwater time synchronization networks and objects.

Underwater Acoustic Sensor Networks find use in critical time-sensitive applications such as disaster prevention and coastline protection. The sensor nodes used in such networks are powered by batteries that are difficult to recharge or replace. Hence it is imperative that routing algorithms used in such networks be very energy efficient while also satisfying necessary delay constraints for time-sensitive applications. Unlike the radio frequency medium, underwater acoustic channels have low bandwidth, large propagation delays and long multipath delay spreads. While energy-efficient routing is an actively researched area for terrestrial radio frequency networks, results from those studies generally do not apply to underwater acoustic networks due to vast differences in channel characteristics. In this paper we explore delay-constrained energy optimization for routing in underwater acoustic sensor networks. Specifically, we propose an offline Mixed Integer Linear Programming based routing algorithm that enables computation of delay constrained energy efficient routes.

In underwater acoustic networks, a transmission is done by means of acoustic wave. However, acoustic transmissions suffer long propagation delay and high bit error rate, especially for real time applications. Since speed of sound and underwater noises are varied with water depth, therefore, this paper takes sound speed and underwater noises into account and proposes a channel-aware depth-adaptive routing protocol, named CDRP, for underwater acoustic sensor networks to relief propagation delay and transmission error rate. In CDRP, the source constructs a virtual ideal path to the sink while it has data to send. According to its one-hop neighbor information, the source then chooses one or several proper forwarders to relay the data. Likewise, the forwarders select next forwarders in the same way until the data is sent to the sink. To our best knowledge, CDRP is the first routing protocol considering the effects of underwater noise and sound speed with depth variation. The simulation results show that CDRP has better performance in end-to-end delay and packet delivery ratio.

Time synchronization is of great significance in underwater acoustic (UWA) networks. Many functions, such as network protocol stack, sleep-scheduling, and localization, are based on time synchronization. Because underwater sound speed is comparatively slow, synchronization protocols encounter a long propagation latency problem, which differs from those in terrestrial sensor networks. As a result, protocols omitting propagation latency, including reference-broadcast synchronization (RBS) and timing-sync protocol for sensor networks (TPSN), are inappropriate underwater. Time synchronization for high latency acoustic networks (TSHL) is a two-phase protocol dealing with the considerable propagation time and performs better than TPSN and RBS. In this paper, a simplified time synchronization protocol based on tiny-sync is introduced. Tiny-sync features low complexity in network bandwidth, storage and processing, and achieves good accuracy in terrestrial networks. However, tiny-sync is time-consuming in UWA networks. We improve the traditional tiny-sync protocol by intensively scheduling message exchange to overcome high propagation latency problem. Simulation results show that improved tiny-sync has better performance in synchronization time than previous protocols, as well as retaining the advantage of small storage requirement in traditional tiny-sync.

Underwater acoustic communication networks can satisfy the need for long-distance reliable communication for underwater node, serving as a key technology for the informatization and intelligentization of such communication. However, due to the use of sound waves as a carrier for information, underwater acoustic networks face complex challenges such as long propagation delays, severe channel attenuation, multipath effects, and environmental noise. To enhance the communication efficiency and reduce network congestion of underwater acoustic networks, this study proposes a MAC protocol based on deep reinforcement learning to adaptively adjust the transmission strategy of network nodes. Each network node collaboratively decides the optimal transmission slot based on its own data buffer status and the history of transmission conflicts, to suppress transmission conflicts and thereby maximize transmission rates. Simulation results show that the designed protocol significantly improves the network throughput while ensuring the fairness of transmission among nodes, providing an important foundation for the rapid exchange of information between underwater nodes.

Due to the limit spectrum resource in the underwater acoustic networks, underwater cognitive acoustic communication is a promising technique. The channel sharing mechanism in cognitive networks can improve the communication capacity efficiently. Jamming attack is a common deny of service attack in cognitive networks. In the underwater cognitive acoustic networks, the anti-jamming problem is quite different from cognitive radio networks. It calls for an effective anti-jamming strategy in the cognitive acoustic channel access. In this article, we propose an online learning anti-jamming algorithm called multi-armed bandit–based acoustic channel access algorithm to achieve the jamming-resilient cognitive acoustic communication. The imperfect channel sensing and the constraints of underwater acoustic communication are considered in the anti-jamming game. Under different kinds of jamming attacks, the channel utilization can be improved with our jamming-resilient approach.

Time synchronization is a supporting technology and necessary precondition for underwater acoustic (UWA) networks. Sensation and actuation in UWA networks need coordination across nodes. Under normal circumstances, the deployment of UWA networks is large, and the energy resources are limited. The existing protocols can’t achieve an accuracy high enough and consume overmuch energy, so they could not well adapt to UWA networks yet. Although many protocols are dedicated to improving accuracy, they often work on the perspective of ameliorating the exchanged mechanism of information and ignore the propagation delay with the greatest impact on accuracy that affected by channel quality. In this paper, we propose a fault tolerant time synchronization protocol. It dedicated to enhancing accuracy by improving the processing method of exchanged synchronization messages and enables the synchronization process adapt to unstable channel quality. The simulation results show that the protocol achieves a high accuracy with low energy cost, and as channel quality deteriorates, compared with existing protocols, its accuracy declines flatter and fluctuates in a smaller range.

Owing to a number of issues, routing in underwater acoustic sensor networks (UASNs) has become a difficult task. First, the distance between nodes in the UASN varies due to their mobility with the water current, increasing the network’s energy usage. The scientific data is taken, and the data packets are transferred over the acoustic network to the onshore base station. Second, due to the dangerous environment, the underwater acoustic network has various obstacles, including longer propagation delays and limited bandwidth availability. The most significant restriction is the inefficient transmission of data packets from the underwater sensor node to the onshore sink node. To attain optimum efficiency, identifying an energy-efficient approach is insufficient. Due to harsh climatic conditions or energy loss, the underwater routing protocol must be able to survive link failure. A new optimization protocol is developed based on the biological inspiration is Hybrid Whale-Lion optimization Algorithm. To overcome all the above-mentioned problems the Hybrid Whale-Lion optimization Algorithm have been proposed. The algorithm is implemented in NS2 simulator, and the performance was compared with buffalo optimization algorithm. The simulation results show throughput, packet delivery ratio, energy efficiency increases and shows better performance when compared with BOA.

With the advances in acoustic modem technology that enabled high-rate reliable communications, current research focuses on communication between various remote instruments within a network environment. Underwater acoustic (UWA) networks are generally formed by acoustically connected ocean-bottom sensors, autonomous underwater vehicles, and a surface station, which provides a link to an on-shore control center. While many applications require long-term monitoring of the deployment area, the battery-powered network nodes limit the lifetime of UWA networks. In addition, shallow-water acoustic channel characteristics, such as low available bandwidth, highly varying multipath, and large propagation delays, restrict the efficiency of UWA networks. Within such an environment, designing an UWA network that maximizes throughput and reliability while minimizing the power consumption becomes a very difficult task. The goal of this paper is to survey the existing network technology and its applicability to underwater acoustic channels. In addition, we present a shallow-water acoustic network example and outline some future research directions.

Originating from the concept of cognitive networks (CNs), which are becoming popular in wireless terrestrial communication scenarios, underwater acoustic cognitive networks (UACNs) are drawing more and more attention in the field of the Internet of Underwater Things (IoUT). However, as the implementation of cognitive mechanisms in underwater acoustic networks is different from that of wireless scenarios, it is impossible or difficult for traditional simulation platforms to carry out simulations of UACNs. There is a lack of specialized simulation tools in terms of UACNs. To enable the quantitative evaluation of the effectiveness and performance enhancement of a UACNs in an adverse underwater environment, a simulation platform of acoustic cognitive networks (SPACNet) was designed and investigated in this article. First, based on a state machine-based protocol programming framework, the SPACNet is capable of supporting the implementation of different state-transform types associated with cognitive networking protocols. Moreover, to facilitate the realization of cognitive function at comprehensive levels of signal, information, and link, an underwater acoustic channel model with an environmental parameter input is integrated in SPACNet to generate underwater environment-driven multiple-aspect behaviors. Moreover, a simplified collision model consisting of an environment factor, channel response, and node location is used to reduce the complexity of the simulation of UACNs signal reception. A simulation was carried out to verify the effectiveness of SPACNet in evaluating the cognitive capabilities of UACNs. Finally, a field UACNs experiment was performed to validate the general consistency between the conclusion obtained with the SPACNet-based simulation and that from the field test.