Acoustic Sensor Networks Research Articles

WLQRP: A Weighting Link-Quality-Based Routing Protocol for Underwater Sensor Networks

Due to challenges posed by long propagation distances, high mobility, limited bandwidth, multipath propagation, and Doppler effects in underwater acoustic sensor networks (UASNs), the design of routing protocols faces numerous complexities. To enhance reliability in sparse node regions and reduce network energy consumption, this paper proposes a dependable and energy-efficient routing protocol termed WLQRP for weighting link-quality-based routing protocol. WLQRP leverages link quality information between nodes for data forwarding. When computing the link quality between nodes, it considers not only the historical transmission success ratio between nodes and their immediate relay but also incorporates the link quality between the relay and the relay’s next-hop nodes. This approach effectively reduces the likelihood of encountering void regions. Moreover, the protocol judiciously selects the next-hop node to improve transmission success rates, thereby minimizing data packet retransmissions and reducing energy consumption. We conduct MATLAB simulations to evaluate the WLQRP protocol, comparing it against the VBF (vector-based forwarding) and the HH-VBF (hop-by-hop vector-based forwarding) underwater routing protocol. Experimental results demonstrate that WLQRP enhances network performance in terms of data transmission rate, energy consumption, and end-to-end delay. These findings validate the efficacy of the proposed protocol.

Joint Channel and Power Assignment for Underwater Cognitive Acoustic Networks on Marine Mammal-Friendly

When marine animals and underwater acoustic sensor networks (UASNs) share spectrum resources, problems such as serious harm caused to marine animals by underwater acoustic systems and scarcity of underwater spectrum resources are encountered. To address these issues, a mammal-friendly underwater acoustic sensor network channel power allocation algorithm is proposed. Firstly, marine animals are treated as authorized users and sensor nodes as unauthorized users. Considering the interference level of sensor nodes on authorized users, this approach improves network service quality and achieves a mammal-friendly underwater communication mechanism. Secondly, to maximize the utility of unauthorized users, the algorithm incorporates a network interference level and node remaining energy into a game-theoretical framework. Using channel allocation and power control, a game model is constructed with a unique Nash equilibrium point. Finally, through simulation, it can be found that the proposed algorithm can obtain a stable optimal power value, and with the increase of network load, the system capacity of the proposed algorithm is significantly improved than that of the traditional cognitive radio technology and the common spectrum allocation algorithm, and the transmitted power of nodes can be controlled according to the size of the residual energy, so as to comprehensively improve the overall performance of the network.

Robust multi-model mobile target localization scheme based on underwater acoustic sensor networks

Underwater mobile target localization based on underwater acoustic sensor networks (UASNs) is a critical application in marine fields. However, the mobility of underwater targets, asynchronous reception of localization information, stratification effects, and unknown measurement losses make UASN-assisted mobile target localization difficult. To address these issues, this study proposes a robust multi-model mobile target localization scheme (RMML) based on UASNs. The RMML suggests a simplified approach for optimal localization reference node selection based on the Cramér-Rao lower bound. This approach improves the localization accuracy of a mobile target by periodically selecting nodes that provide high-quality localization references. Using the localization reference provided by the selected nodes, a robust mobile target localization algorithm is developed based on an interacting multiple model and unscented Kalman filter. In this algorithm, a multipoint prediction method and ray tracing method are jointly proposed to improve the target state estimation accuracy under the asynchronous reception of localization information and the stratification effect. Maximum a posteriori probability estimation is used to estimate measurement loss, and pseudo-residuals are constructed based on the estimated measurement loss to improve the localization accuracy and robustness of the algorithm. Finally, extensive simulations and experiments are performed to verify the effectiveness of the RMML.

Low Power Wake-Up Receivers for Underwater Acoustic Wireless Sensor Networks

This article reports two low power wake-up receiver (WuRx) circuits (Type A and B) for underwater acoustic wireless sensor networks. The proposed circuits realize the same novel method to extract the wake-up call from the acoustic signals received by a sensor node using different circuit topologies. This is accomplished by comparing the amplitude and the duration of the received pulses to a predefined code. A combination of these two parameters provides a safe and robust decoding system. The values and duration of the predefined code can be adjusted by tuning the biasing voltages in the circuits. The main advantages of the presented designs are modularity and tunability. To verify the operation of the proposed system, an ASIC has been realized. The WuRxs have been characterized in terms of tuning, duty cycle, and power consumption. Both WuRxs can consume less than 0.5. Type A occupies an area of mode = text0.058mm2, has a data rate of mode = text250bit/s, and presents the lowest power consumption reported, consuming 265nW and 61nW in active and sleep modes, respectively.

FER-Restricted AUV-Relaying Data Collection in Underwater Acoustic Sensor Networks

Relaying is an effective method to achieve reliable and timely data collection, which is one of the most important parts of underwater acoustic sensor networks (UASNs). Considering that the relay position determines the reliability of relay communication, we study the problem of relay placement and place an autonomous underwater vehicle (AUV) to mobile relay data transmission and realize the reliable, low-latency, and low-energy data collection in UASNs. First, we formulate the relay positions that can meet a certain frame error rate (FER) requirement as the FER-restricted area (FRA), and approximate FRA with a three-dimensional geometry formula. The problem of reliable and timely data collection becomes planning a short AUV relaying trajectory under the FRA constraint. To this end, we propose a nearest-community (N-C) trajectory planning algorithm to design the AUV relay trajectory. A member grouping method and the necessity of position (NoP) concept are proposed to further reduce the relay positions and trajectory length of the AUV. Simulation results verify that the approximate FRA is more than 90% consistent with the real FRA and show that the N-C using NoP-based member grouping can successfully receive more packets per minute and consume fewer sensors’ energy than other algorithms.

A diffusion filtered-x affine projection algorithm for distributed active noise control

The well-known Filtered-x Affine Projection (FxAP) algorithm is usually deemed a better choice than the conventional Filtered-x Least-Mean-Square (FxLMS) algorithm when faster convergence speed is desired in active noise control applications. However, the improvement of its convergence performance is obtained at the expense of increased computational complexity. It is usually unrealistic to regulate multichannel ANC systems using the centralized AP algorithm. Recently, distributed diffusion adaptation schemes over acoustic sensor and actuator networks have been introduced to multichannel ANC systems, such as the Diffusion FxLMS algorithms. Distributed processing based on diffusion cooperation strategy allocates the computation load to the network nodes in a scalable manner. This paper proposes a distributed Diffusion Filtered-x AP (DFxAP) algorithm for multichannel ANC systems. Simulation results and computational complexity analysis show that the DFxAP algorithm outperforms the Diffusion FxLMS algorithm in convergence performance and has lower computational complexity compared to the centralized AP algorithm.

A cross-layer approach for load balancing and energy-efficient QoS-based routing reliability for UWSN

Considering several fundamental needs of network performance, the Routing and Media Access Control (MAC) layers are crucially checked out for their operations. Sometimes, MAC protocol faces difficulties in modifying the situations over underwater communication which are specifically considered to be dynamic. The nodes in water tend to remain unstable and network fluctuations are made depending upon the number of competitors. The existing hybrid MAC protocol does not possess dynamic network loads. It also involves a lack of modification in access control approaches which provide variations in network loads. Finally, it leads to delayed network performance. The routing layer focus on some difficult parameters like increased packet loss, restricted bandwidth with substantial energy incursion, reduced network lifetime, increased propagation delay, less remaining energy, consistent data transfer, and energy organization which are considered to be the most important research issues in Underwater Acoustic Sensor Networks (UWASNs). In MAC and routing layers, a Cross-layer approach involves some techniques which are discussed and implemented using Ns3 simulation to obtain the performance report. It is also proposed to compare the algorithm with existing techniques to provide accurate results. Reinforcement Learning (RL) in the MAC layer for SINR-based time slot allocation and Integrated Artificial Fish Swarm with Bacterial Foraging Algorithm (IAFSBFA) for energy-aware QoS reliable routing in the network layer are used in this system. In this cross-layer approach, load balancing in the MAC layer and efficient routing using a hybrid algorithm gives out better performance in the underwater network.

Dingo optimization influenced arithmetic optimization – Clustering and localization algorithm for underwater acoustic sensor networks

Underwater acoustic sensor networks (UASNs) are quickly being used in environmental monitoring, marine life observation, and underwater resource research. This paper introduces the Dingo Optimisation Influenced-Arithmetic Clustering and Localisation Algorithm. The proposed method was developed due to the above considerations. DOIAO-CLA combines Dingo Optimisation (DO) and Arithmetic Optimisation (AO), two powerful optimisation methods. DOIAO-CLA uses DO's robust exploration and exploitation features to group sensor nodes with similar propagation characteristics. It also optimises cluster formation and reduces distance discrepancies using AO. DOIAO-CLA also enables reliable localization by merging distance- and angle-based methods. DO optimises node localization by using distance and angle of arrival data. This integration enhances UASN node localization accuracy and reliability. The DOIAO-CLA was tested against other clustering and localization algorithms like Archimedes Optimisation Algorithm (AOA), Squirrel Search Algorithm (SSA), Hybrid Cat Cheetah Optimisation Algorithm (HCCOA), Ant Colony Optimisation Algorithm (ACOA), Grey Wolf Optimisation Algorithm (GWOA), and Particle Swarm Optimisation Algorithm. According to the results, DOIAO-CLA taps alternatives for network robustness, data aggregation, and localization precision. Finally, DOIAO-CLA solves the UASN clustering and localization problem in a novel and effective way.

An Energy-Efficient Multimode Transmission Scheme for Underwater Sensor Network

Underwater sensor network plays a critical role in the ocean data collection owing to its capability of providing reliable and wide communication coverage. How to assure lifetime performance of the network with limited energy supply has always been a key research issue. In this paper, we propose an underwater acoustic sensor network model which supports data delivery from each underwater sensor node (USN) to sea surface sink node (SN) in either direct or relay-assisted transmission mode, i.e., transmission mode between each USN and the SN can be dynamically selected according to network’s current state. To optimize its lifetime performance, we model the mode selection and resource allocation issue jointly into a non-convex and mixed integer programming problem. In order to efficiently solve it, we further divide the original problem into two subproblems: resource allocation subproblem and joint mode and relay selection subproblem. We prove that the reformulated non-convex resource allocation problem can be equivalent to a convex optimization problem, and its optimal solution can be found by using Lagrange dual decomposition method. For the second subproblem, some critical conditions are analyzed to determine optimal relays with the criterion of balancing energy consumption between USNs and a matching approach is designed to obtain the mode and relay selection results based on USNs’ priorities. Simulation results validate that the proposed transmission scheme is effective and superior to the traditional time division multiple access scheme.

An Adaptive Routing Protocol for Underwater Acoustic Sensor Networks With Ocean Current

An Adaptive Routing Protocol for Underwater Acoustic Sensor Networks With Ocean Current

Energy-Aware Framework for Underwater Mine Detection System Using Underwater Acoustic Wireless Sensor Network

Underwater mines are considered a major threat to aquatic life, submarines, and naval activities. Detecting and locating these mines is a challenging task, due to the nature of the underwater environment. The deployment of underwater acoustic sensor networks (UWASN) can provide an efficient solution to this problem. However, the use of these self-powered sensors for intensive data sensing and wireless communication is often energy-scaring and might call into question the viability of their application. One attractive solution to extend the underwater wireless sensor network will be the adoption of cluster-based communication, since data processing and communication loads are distributed in a timely manner over the members of the cluster. In this context, this study proposes an energy-efficient solution for high-accuracy underwater mine detection based on the adequate clustering approach. The proposed scheme uses a processing approach based on wavelet transformation to extract relevant features to efficiently distinguish mines from other objects using the Naïve Bayes algorithm for classification. The main novelty of this approach is the design of a new low-complexity scheme for efficient sensor-based acoustic object detection that outperforms most of the existing solutions. It consumes a low amount of energy, while ensuring 95.12% target detection accuracy.

Pilot Agent-Driven Wireless Acoustic Sensor Network for Uninterrupted Data Transmission

Wireless acoustic sensor networks (WASN) usually demand uninterrupted and reliable data transmissions and an efficient path from the source nodes to the destination nodes, thus ensuring reliable delivery of sensitive or critical data with the use of multipath routing protocols. This paper presents a novel agent-driven WASN relying on a set of static and mobile agents. In the proposed technique, the location address is functioned into the operating node and the destination node. Calculations of the midpoint between the operating and the destination nodes are followed by identifying the shortest path based on a reference axis, using a mobile agent and a location address. Such an approach aims to ensure maximum utilization of the communicating paths. Based on the information concerning partial topology of the network, the destination node computes the weight factor and multiple paths using node distances, energy ratios and efficiencies of specific links. Then, the destination node selects the appropriate path from the multiple paths available, to transmit the data. This article also analyzes the performance of the proposed system with various parameters taken into consideration and shows its efficiency in comparison to other existing techniques.

Impact of moving target on underwater positioning by using state measurement

The localization of moving targets in an underwater acoustic wireless sensor network (UAWSN) is inaccurate due to the various underwater forces (viscous, hydrodynamic forces, perturbation of underwater). The false measurements in the sensor network cause position errors and velocity errors which disrupt the localization of the moving target. A randomly fluctuated spillover effect is introduced in the present paper. The absorption losses generated due to the spillover effect cause false measurements of the moving target. Theorem 1 describes the genesis of these absorption losses and their consequences in UAWSN. The measurements from each moving target in the presence of absorption losses are formulated in the elliptical region. A joint probabilistic data association (JPDA) method is proposed to quantify the false measurements in the elliptical region. A moving target state estimation (MTSE) algorithm is proposed to eliminate the false measurements from the moving targets and to measure the localization of moving targets with the help of the propagation speed of targets. The theoretical measurements of position RMSE and velocity RMSE are verified with standard methods. The proposed MTSE method improves the localization performance of the moving targets by 29.42 % and reduces 32.16 % of position errors and 36.23 % of velocity errors up to 550 ​m. The proposed algorithm will be useful for the sub-aquatic Internet of underwater things (IoUT).

Energy-efficient data collection over underwater MI-assisted acoustic cooperative MIMO WSNs

Underwater magnetic induction (MI)-assisted acoustic cooperative multiple-input-multiple-output (MIMO) has been recently proposed as a promising technique for underwater wireless sensor networks (UWSNs). For the more, the energy utilization of energy-constrained sensor nodes is one of the key issues in UWSNs, and it relates to the network lifetime. In this paper, we present an energy-efficient data collection for underwater MI-assisted acoustic cooperative MIMO wireless sensor networks (WSNs), including the formation of cooperative MIMO and relay link establishment. Firstly, the cooperative MIMO is formed by considering its expected transmission range and the energy balance of nodes with it. Particularly, from the perspective of the node's energy consumption, the expected cooperative MIMO size and the selection of master node (MN) are proposed. Sequentially, to improve the coverage of the networks and prolong the network lifetime, relay links are established by relay selection algorithm that using matching theory. Finally, the simulation results show that the proposed data collection improves its efficiency, reduces the energy consumption of the master node, improves the networks' coverage, and extends the network lifetime.

A Backbone-Network-Construction-Based Multi-AUV Collaboration Source Location Privacy Protection Algorithm in UASNs

Underwater acoustic sensor networks (UASNs) are effective instruments for monitoring marine environments and surveying seabed resources, it is important to improve their security protection, including source location privacy protection. Numerous strategies have been presented by researchers to strengthen location privacy, however, the majority of these plans have expensive energy costs. Therefore, a backbone network construction-based multi-autonomous underwater vehicle (AUV) collaboration source location privacy protection (BNCSLP) algorithm has been enhanced to address this issue. First, the nodes in the network are split into various clusters, and an entire network is segmented into various regions. The backbone network is built using clusters that house the source. To prevent the adversary’s tracking, the AUV alternately chooses alternative backbone nodes and relays the source and fake data. Then, the cluster head determines whether to update the clusters by calculating how similar the data are with nearby clusters. The nearest neighbor technique is used by the updated cluster to anticipate the data and to reduce the energy utilization of forwarding the data packets, resulting in that there is less chance of data packets being intercepted and the source location being revealed. Finally, the AUV re-plans the trajectory, which shortens the AUV’s travelling path because only fewer cluster heads need to be accessed, decreasing the time it takes for data to be transmitted.

Vortex‐induced vibration effects in underwater acoustic wireless sensor networks

AbstractA randomly fluctuated vortex‐induced vibration (VIV) affects the localization of moving targets in an underwater acoustic wireless sensor network (UAWSN) to cause an offset time and time synchronization error which disturbs the localization of the non‐cooperative moving target. Definition 1, Theorem 1 has been introduced in the present work to describe the genesis and consequences of the VIV effect in UAWSN. An elliptic localization introduces the direct and indirect path measurements of the moving target. The standard Crammer Rao lower bound parameter quantifies the VIV effect. The compensation of vortex‐induced vibrations (CVV) algorithm is proposed to quantify the degradation of localization performance and to estimate the position of the moving target. The theoretical measurements of position error, velocity error with respect to the variation of noise, number of receiver sensors, and probability of line of sight errors are compared to the standard methods. The proposed CVV algorithm improves the localization performance by 32.24% and reduces 34.36% of position errors, and 37.46% of velocity errors up to 600 m. It can be useful for the sub‐aquatic internet of underwater things.

Joint Slot Scheduling and Power Allocation for Throughput Maximization of Clustered UASNs

In the last decades, independent consideration of underwater acoustic medium access control (MAC) layer has received much attention for designing a reliable data transmission protocol. Although it can simplify the system design, it is often insufficient for the enhancement of overall system performance. The focus of this paper is on the cross-layer optimization to maximize the network throughput (NT) of clustered underwater acoustic sensor networks (UASNs) by jointly optimizing the sensor nodes’ slot scheduling and power allocation. The formulated problem is a mixed integer non-linear programming problem, which is NP-hard. An alternating-optimization-based centralized algorithm is proposed first to solve it, which can achieve the best NT performance but at the price of high complexity. Therefore, a multi-leader multi-follower Stackelberg game based distributed algorithm is also proposed to achieve a better tradeoff between system performance and complexity. Simulation results demonstrate that our proposed schemes considering the information causality constraint have a better NT performance than those without a “systematic” consideration over such joint optimization, like CMS-MAC algorithm.

LSLPR: A Layering and Source-Location-Privacy-Based Routing Protocol for Underwater Acoustic Sensor Networks

LSLPR: A Layering and Source-Location-Privacy-Based Routing Protocol for Underwater Acoustic Sensor Networks

A QoS-Aware Energy-Efficient Chimp Optimization Routing Protocol with Efficient Sensor Node Deployment Strategy in Underwater Acoustic Sensor Network

As an extension of wireless sensor networks in the underwater environment, Underwater Acoustic Sensor Networks (UASNs) have led to a broad consideration of academicians. One of the problems that lower UWSN effectiveness in terms of network lifespan is premature energy depletion. It might be caused by the network nodes using different amounts of energy. In UASNs, the effectiveness and dependability of data transfer remain so adverse because of the intricate underwater environment in diverse ocean applications like surveilling atypical submarine oil pipelines. Inspired by the significance of UASNs’ quality of service in several implementations, this study proffers a metaheuristic optimization algorithm (AG) called Chimp Optimization-based Routing Protocol (CH-ORP) for UASNs obtaining intricate features of underwater (UW) medium into concern like 3D changing topology, high propagation delay, node mobility, and density, and, also, cluster head nodes’ rotation mechanism. Initially, the entire network (NW) paradigm has been considered as a three-dimensional cube out of a grid point of view, and the three-dimensional cube has been split into several little cubes by employing Delaunay Triangulation. The optimization has been carried out for lessening node failure rate and NW energy consumption rate by ideally placing the sensor nodes in UW acoustic communication. The NW topology’s steadiness has been assured by the AG, and this optimizes the node redeployment scheme by computing the fitness function for all nodes. The proffered AG’s simulation substantiations have been performed for exhibiting the CH-ORP’s efficiency that executes finer when compared to the advanced methodologies concerning energy efficiency, reliability, and end-to-end delay. It has been found that the proposed Ch-ORP achieves 698 packets received with 28% of energy consumption, 156-sec Network delay, 257 packet loss, 97.23% of PDR, and 1256 Mbps of Network throughput.

Secured Clustering Multilevel Underwater Acoustic Networks with Dynamic Routing Discovery (SCDRD) Protocol

Abstract: Due to multiple rising automated industry and combat field applications, researchers have developed a growing interest in the area of Underwater Acoustic Sensor Networks (UASNs) over the previous decade. Extending the lifetime of the energy and the consumption of energy in UASNs are enormous challenges. One of the primary difficulties in UASNs is the development of energy-saving routing mechanisms. In recent days the security of the data collected is the main concern because of widely accessible wireless sensors, because these low-power devices are incompatible with complicated encryption methods. As a result, for multi-hop Underwater Acoustic Sensor Networks (UASNs) with non-replenish able energy resources, lifetime optimization and security are two opposing design concerns. This work introduces an Efficient Energy Clustering with Dynamic Routing Discovery protocol (SCDRD protocol), which addresses two competing difficulties by taking into account several characteristics such as probability random walking and the energy balance control mechanism. The suggested protocol detects that energy consumption in the existing network topology is disproportional to energy deployment, which has an impact on the lifetime of wireless sensor networks. Through a quantitative security analysis, this work proposes a non-uniform efficient deployment technique to handle existing energy resource optimization problems and addresses the security location privacy concern. In all circumstances, the proposed Protocol produces the efficient trade-off between the energy balance and the routing mechanisms, allowing sensor networks to last substantially longer. In addition, the deployment of energy in the non-uniform manner results in the increased network’s lifetime and overall packets sent. The results of proposed work is compared with existing cost-aware routing protocols and outperform the existing protocol with respect to various performance parameters like energy, throughput and delivery ratio.