Underwater Sensor Networks Research Articles

AUV-Aided Optical—Acoustic Hybrid Data Collection Based on Deep Reinforcement Learning

Autonomous underwater vehicles (AUVs)-assisted mobile data collection in underwater wireless sensor networks (UWSNs) has received significant attention because of their mobility and flexibility. To satisfy the increasing demand of diverse application requirements for underwater data collection, such as time-sensitive data freshness, emergency event security as well as energy efficiency, in this paper, we propose a novel multi-modal AUV-assisted data collection scheme which integrates both acoustic and optical technologies and takes advantage of their complementary strengths in terms of communication distance and data rate. In this scheme, we consider the age of information (AoI) of the data packet, node transmission energy as well as energy consumption of the AUV movement, and we make a trade-off between them to retrieve data in a timely and reliable manner. To optimize these, we leverage a deep reinforcement learning (DRL) approach to find the optimal motion trajectory of AUV by selecting the suitable communication options. In addition to that, we also design an optimal angle steering algorithm for AUV navigation under different communication scenarios to reduce energy consumption further. We conduct extensive simulations to verify the effectiveness of the proposed scheme, and the results show that the proposed scheme can significantly reduce the weighted sum of AoI as well as energy consumption.

Efficient Routing Protocol with Localization Based Priority & Congestion Control for UWSN

The nodes in the sensor network have a wide range of uses, particularly on under-sea links that are skilled for detecting, handling as well as management. The underwater wireless sensor networks support collecting pollution data, mine survey, oceanographic information collection, aided navigation, strategic surveillance, and collection of ocean samples using detectors that are submerged in water. Localization, congestion routing, and prioritizing the traffic is the major issue in an underwater sensor network. Our scheme differentiates the different types of traffic and gives every type of traffic its requirements which is considered regarding network resource. Minimization of localization error using the proposed angle-based forwarding scheme is explained in this paper. We choose the shortest path to the destination using the fitness function which is calculated based on fault ratio, dispatching of packets, power, and distance among the nodes. This work contemplates congestion conscious forwarding using hard stage and soft stage schemes which reduce the congestion by monitoring the status of the energy and buffer of the nodes and controlling the traffic. The study with the use of the ns3 simulator demonstrated that a given algorithm accomplishes superior performance for loss of packet, delay of latency, and power utilization than the existing algorithms.

Quadratic ensemble weighted emphasis boosting based energy and bandwidth efficient routing in Underwater Sensor Network

Underwater Sensor Network (UWSN) is a network that comprises a large number of independent underwater sensor nodes to perform monitoring tasks over a given area. UWSN minimized propagation delay, bandwidth, and packet loss. However, the implementation of efficient communication is a significant problem at UWSN. Therefore, Energy and Bandwidth-aware Quadratic Ensemble Weighted Emphasis Boosting Classification (EB-QEWEBC) method for performing energy-efficient routing in UWSN is proposed. Initially, different numbers of underwater sensor nodes are considered as input. Next, the bandwidth and energy consumption of every underwater sensor node is measured. After that, classification between underwater sensor nodes is made by considering energy and bandwidth as factors using Regularized Quadratic Classifier (i.e., weak classifier) for performing routing with minimum delay. Followed by, Weighted Emphasis Boosting is utilized to ensemble weak learners to form strong learners for improving data routing performance results with the biconvex combination. Finally, after classifying the node, data packets are sent to higher energy and bandwidth-efficient underwater sensor nodes. The classification process is carried out at every underwater sensor node for transmitting data packets to the sink node with minimum delay. This method determines the energy-efficient data communication through classification and boosting to reduce the misclassification rate. Experimental results EB-QEWEBC shows a minimization of 14%, 21%, 26%, and 54% in terms of bandwidth, energy consumption, end-to-end delay, and misclassification rate as compared to state-of-art-methods respectively.

FSE2R: An Improved Collision-Avoidance-based Energy Efficient Route Selection Protocol in USN

The 3D Underwater Sensor Network (USNs) has become the most optimistic medium for tracking and monitoring underwater environment. Energy and collision are two most critical factors in USNs for both sparse and dense regions. Due to harsh ocean environment, it is a challenge to design a reliable energy efficient with collision free protocol. Diversity in link qualities may cause collision and frequent communication lead to energy loss; that effects the network performance. To overcome these challenges a novel protocol Forwarder Selection Energy Efficient Routing (FSE2R) is proposed. Our proposal’s key idea is based on computation of node distance from the sink, Residual Energy (RE) of each node and Signal to Interference Noise Ratio (SINR). The node distance from sink and RE is computed for reliable forwarder node selection and SINR is used for analysis of collision. The novel proposal compares with existing protocols like H2AB, DEEP, and E2LR to achieve Quality of Service (QoS) in terms of throughput, packet delivery ratio and energy consumption. The comparative analysis shows that FSE2R gives on an average 30% less energy consumption, 24.62% better PDR and 48.31% less end-to-end delay compared to other protocols.

Priority based [formula omitted]-coverage hole restoration and [formula omitted]-connectivity using whale optimization scheme for underwater wireless sensor networks

Coverage hole restoration and connectivity is a typical problem for underwater wireless sensor networks. In underwater applications like underwater oilfield reservoirs, undersea minerals and monitoring etc., where nodes face many hurdles and are unable to cover the required region during a natural disaster such as tsunami, flood, earthquakes, and environmental interference. It creates a coverage hole and consumes high energy with bad network quality. This problem considered as an NP-complete problem where a set of sensor nodes is required to identify the k-coverage hole and m-connectivity. In the literature, researchers have not focused on k-coverage hole restoration and m-connectivity issues during natural disasters and environmental interference. To mitigate this problem, we proposed priority-based coverage hole restoration and -connection using a whale optimization scheme to restore coverage holes and extract relevant information for the construction of undersea oilfield reservoirs, minerals, and mines. In this scheme, we identified the list of k-coverage holes and addressed autonomous underwater vehicles (AUVs) to place the additional mobile nodes in an appropriate coverage hole. A novel multi-objective function is formulated to obtain the optimal path for AUVs. Furthermore, while restoring coverage holes, we checked the connectivity of nodes. In the network, each node coordinated sleep scheduling with neighbor nodes to maintain energy efficiency. Performance evaluation of the proposed scheme shows better results than the existing schemes under different network scenarios which provide maximum coverage and connectivity, less energy consumption with a high convergence rate.

Analysis of CoDBR and CEEDBR Protocols in Underwater Wireless Sensor Networks

UWSNs (underwater wireless sensor networks) are essential for doing any type of task underwater. Huge broadcast lag, great error degree, small bandwidth, and restricted energy in Underwater Sensor Networks interest concentration of utmost investigators. In UWSNs, the efficient use of energy is one of the main problems, as the substitution of energy sources in this kind of location is extremely costly. UWSNs are utilized in many fields, like measuring pollution, issuing tsunami cautions, conducting offshore surveys, and strategic tracing. For numerous functions, the efficacy and dependability of network regarding prominent operation, energy preservation, small bit error rate, and decreased interruption are fundamental. Nevertheless, UWSN’s exclusive features like small bandwidth accessibility, large interruptions in broadcast, very vivacious network topology, and extreme possibility of error present numerous problems in the growth of effective and dependable communication procedures. As opposed to current deepness-based routing techniques, we are focusing on CoDBR (Cooperative Depth-based Routing) and CEEDBR (Cooperative Energy Efficient Depth-based Routing) procedures to improve network lifespan, energy efficacy, and amount.

Analysis of CoDBR and CEEDBR protocols in underwater wireless sensor networks

Underwater wireless sensor networks (UWSNs) are essential for doing any type of task underwater. Huge broadcast lag, great error degree, small bandwidth, and restricted energy in Underwater Sensor Networks interest concentration of utmost investigators. In UWSNs, the efficient use of energy is one of the main problems, as the substitution of energy sources in this kind of location is extremely costly. UWSNs are utilized in many fields, like measuring pollution, issuing tsunami cautions, conducting offshore surveys, and strategic tracing. For numerous functions, the efficacy and dependability of network regarding prominent operation, energy preservation, small bit error rate, and decreased interruption are fundamental. Nevertheless, UWSN’s exclusive features like small bandwidth accessibility, large interruptions in broadcast, very vivacious network topology, and extreme possibility of error present numerous problems in the growth of effective and dependable communication procedures. As opposed to current deepness-based routing techniques, we are focusing on CoDBR (Cooperative Depthbased Routing) and CEEDBR (Cooperative Energy Efficient Depth-based Routing) procedures to improve network lifespan, energy efficacy, and amount

A Study of the Accuracy of Positioning in a Network of Wireless Underwater Sensors Depending on the Genetic Algorithm

Wireless Sensors Networks (WSNs) are a scientific revolution in wireless communications and embedded systems. WSN is based on the idea of abandoning the human factor, which was often an obstacle because it was not possible to be in the places where these networks are placed, especially if the collection of information required a long time, Underwater wireless sensor nodes can be deployed for monitoring, exploration, and for disaster protection, and this is what is called Underwater Wireless Sensor Networks (UWSNs). nIn this paper, we will study how the parameters of the genetic algorithm change when locating sensors under water, Including the error rate, the number of nodes in the network and the time taken to implement.

Direct-Conversion Spectrum Sensor Impaired by Symmetric α-Stable and α-Sub-Gaussian Noises

Spectrum sensing in underwater cognitive acoustic networks or in underwater acoustic sensor networks can be impaired by impulsive noise generated by snapping shrimps. In mathematical analysis or simulations, the amplitude variations of this noise are commonly modeled by the symmetric alpha-stable (SαS) distribution. As an alternative, the alpha-sub-Gaussian (αSG) distribution can model both temporal correlation and amplitude variations. This article assesses the performance of underwater spectrum sensing with a direct-conversion receiver (DCR) under impulsive noise modeled by the SαS and αSG distributions. Several recent test statistics are compared, demonstrating that they have different degrees of robustness against impulsive noise and that the DCR is significantly less sensitive to this noise, compared to the conventional receiver model that does not take into account the influences of hardware characteristics into the performance of spectrum sensing.

Energy efficient hybrid ARQ scheme for cooperative communication in underwater acoustic sensor networks

Energy efficient hybrid ARQ scheme for cooperative communication in underwater acoustic sensor networks

Hop-based void avoidance routing protocol for underwater acoustic sensor networks

Hop-based void avoidance routing protocol for underwater acoustic sensor networks

Energy efficient hybrid ARQ scheme for cooperative communication in underwater acoustic sensor networks

Energy efficient hybrid ARQ scheme for cooperative communication in underwater acoustic sensor networks

Hop-based void avoidance routing protocol for underwater acoustic sensor networks

Hop-based void avoidance routing protocol for underwater acoustic sensor networks

Traffic Sensors Selection for Complete Link Flow Observability through Simulated Annealing

Sensor selection is a key issue in sensor network design. Due to limited equipment and maintenance costs, and to minimize processing and communication overhead, only a limited number of sensors can reasonably be used, and they must also be reasonably placed. Indeed, the selection of an appropriate number of physical sensors is critical to ensure reliable estimates when monitoring large-scale systems such as traffic flows, water or gas transport infrastructures, or underwater wireless sensor networks. Regarding traffic systems, the full link flow observability problem consists of selecting the minimum number of traffic sensors to be installed from a given larger set (Salari, 2019). In particular, it involves selecting a subset of p, possibly redundant, sensors from a larger set of n ≫ p potential sensors in order to preserve the structural observability property of the entire traffic network. To solve this problem, the classical concept of system observability is exploited as a criterion for sensor selection. In this paper, we refer to the design of a simulated annealing heuristic to approximately solve the problem. The resulting subset of sensors is then used to design a Luenberger observer to properly estimate the system state. Some numerical simulations demonstrate the effectiveness of the proposed approach.

Social Internet of Things: Ethical AI Principles in Trust Management

Trust management has become a fundamental requirement for Social Internet of Things (SIoT) to enable a trustworthy social network of smart objects necessary for enhancing the security and reliability of cyber-physical systems. To increase the credibility scores in trust management, AI (Artificial Intelligence) has been adopted. However, the current need for digital acceleration has brought ethical concerns related to the smartness and social consciousness of autonomous objects, which leads to a question whether AI-based trust management is ready to deal with these concerns. In this paper, we consider 11 ethical dimensions within the context of trust management in SIoT. Then, we examine the existing AI-based trust models in the context of SIoT and its related application domains to assess their maturity in terms of the 11 ethical dimensions. The evaluation results show how trust management can be improved by AI ethical principles in vehicular networks and underwater acoustic sensor networks.

A Survey of Sybil Attack Countermeasures in Underwater Sensor and Acoustic Networks

A Survey of Sybil Attack Countermeasures in Underwater Sensor and Acoustic Networks

Cooperative retransmission-based MAC method for underwater sensor networks

Cooperative retransmission-based MAC method for underwater sensor networks

Formal Verification of a MAC Protocol for Underwater Sensor Networks

Formal Verification of a MAC Protocol for Underwater Sensor Networks

MAC Protocol for Two-Tier Underwater Wireless Networks With Distance-Dependent Propagation Delay Variation

In this paper, we consider a two-tier communication scenario for the data transmission of underwater sensor network. The underwater sensor nodes form single-hop clusters around the gateway nodes and communicate with them via acoustic wireless links, while the gateway nodes communicate to the remotely located sink node directly via radio frequency (RF) wireless links. Thus, the field data is collected at the sink node via two-hop communication links. The first hop acoustic communication link is characterized by long propagation delay and distance-dependent delay variance, whereas the second hop is considered to be connected by satellite links which is characterized by long propagation delay but negligible propagation delay variance. We use ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$X$ </tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Y$ </tex-math></inline-formula> ) to denote that medium access control (MAC) protocol <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$X$ </tex-math></inline-formula> is used at first hop and MAC protocol <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Y$ </tex-math></inline-formula> is used at second hop. For the first hop communication, we propose and analyze the performance of dynamic reservation protocol (DRP) in presence of transmitter-receiver distance-dependent propagation delay variance. Then, considering TDMA-reservation protocol (TRP) in the second hop, we analyze (DRP, TRP) protocol performance at the sink. Further, we study the optimum cluster size that maximizes the overall network utilization and compare the performance with the (Aloha, Aloha) protocol. We show that, for Exponentially distributed large message the utilization of our protocol set (DRP, TRP) is approximately thrice the utilization of (Aloha, Aloha) protocol. Also, the delay of (DRP, TRP) is significantly less than the delay of (Aloha, Aloha) with long message size as well as with high load scenario. The analytical results are supported by discrete event based random network simulation studies.

Underwater Acoustic Sensor Network Data Optimization with Enhanced Void Avoidance and Routing Protocol

Deployment of a multi-hop underwater acoustic sensor network (UASN) in a larger region presents innovative challenges in reliable data communications and survivability of network because of the limited underwater interaction range or bandwidth and the limited energy of underwater sensor nodes. UASNs are becoming very significant in ocean exploration applications, like underwater device maintenance, ocean monitoring, ocean resource management, pollution detection, and so on. To overcome those difficulties and attains the purpose of maximizing data delivery ratio and minimizing energy consumption of underwater SNs, routing becomes necessary. In UASN, as the routing protocol will guarantee effective and reliable data communication from the source node to the destination, routing protocol model was an alluring topic for researchers. There were several routing techniques devised recently. This manuscript presents an underwater acoustic sensor network data optimization with enhanced void avoidance and routing (UASN-DAEVAR) protocol. The presented UASN-DAEVAR technique aims to present an effective data transmission process using proficient routing protocols. In the presented UASN-DAEVAR technique, a red deer algorithm (RDA) is employed in this study. In addition, the UASN-DAEVAR technique computes optimal routes in the UASN. To exhibit the effectual results of the UASN-DAEVAR technique, a wide spread experimental analysis is made. The experimental outcomes represented the enhancements of the UASN-DAEVAR model.