Nodes In Underwater Sensor Networks Research Articles

Deployment Strategy Analysis for Underwater Geodetic Networks

Seafloor geodetic network (SGN) is the foundation for building an underwater positioning, navigation and timing (PNT) system. Traditional network deployment mainly focuses on the deployment of underwater sensor network nodes. However, for SGN, there is no surface buoy node and submarine buoy node, and the number of anchors is limited because it is quite expensive to fully cover large scale areas. To achieve wide coverage and good positioning service of each set of underwater base stations, we focus on the network design of a single set of reference stations in this paper. We propose several deployment plans for a local SGN and then analyze their service quality indicators by considering the stratification effect caused by non-uniformly distributed sound speed. To evaluate the performance of each topology of SGN, we compare their coverage range, horizontal dilution precision (HDOP) and accuracy performance of positioning tests. Based on the overall performance in our simulation, we believe that the star five-node topology is a good topology design under sufficient economic conditions.

Doppler shift with Archimedes Optimization Algorithm for localizing unknown nodes in underwater sensor networks

SummaryThe issue of underwater sensor network (UWSN) localization has led to the aim of techniques presented in recent years. In this paper, we develop Doppler shift with Archimedes Optimization Algorithm for localizing unknown nodes in UWSN. The projected method predicts that sink node plays a major function in managing the computational load contrasted with the remaining nodes in the network of underwater. This node localization is proceeding with frequency shifts of sound waves contrasted toward real, which are present once observer in addition source can be mobile as they do in a marine atmosphere. The proposed technique is utilized to compute the estimated position of an unknown sensor node; here Archimedes' optimization algorithm is utilized to reduce the error during localization of nodes in UWSNs. This proposed technique can be enhancing the accuracy of the localization of nodes in UWSNs. This proposed methodology can be implemented and evaluated with the help of performance metrics. To validate the proposed technique's efficiency, it is contrasted with conventional techniques like Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA).

Energy-Efficient Routing Protocol for Selecting Relay Nodes in Underwater Sensor Networks Based on Fuzzy Analytical Hierarchy Process.

The use of underwater sensor networks (UWSNs) offers great advantages in many automatic observation services such as water monitoring (ocean, sea, etc.) and registering of geological events (landslides, earthquakes). However, UWSNs have many more limitations than terrestrial sensor networks (smaller bandwidth, higher delays, etc.) with new requirements such as low power consumption by nodes or being able to select appropriate routes in a dynamic topology due to water currents and movements. To cope with these problems, the use of a routing protocol is very important. In this paper we propose a routing technique that adapts to changes in the network topology, avoiding multiple retransmissions that would affect its overall performance. This protocol is energy-efficient and is implemented using a fuzzy analytical hierarchical process (FAHP) under multi-criteria decision making (MCDM) to make an intelligent routing decision based on objectives, criteria and alternatives. To select the next node on the route, several comparison matrices are used: number of hops, distances to the sink node, and number of neighbors. The results show that the proposed setup behaves similarly to other existing underwater sensor network routing schemes using fuzzy schemes such as SPRINT.

Localization and correction of location information for nodes in UWSN-LCLI

Location is essential to identify the floating senor nodes in underwater. Underwater Sensor Networks (UWSNs) enable various critical applications like monitoring underwater environment, flora and fauna, sea life, exploration such as earthquake, disaster mitigation, motion tracking. In many cases, an underwater sensor node is necessary. Some points make the underwater study different and slightly complex. The first point is that radio signal cannot detect the underwater environment, despite radio waves acoustic signals used, which runs due to water currents. The second point is that earthy networks are deployed in the 2D environment, but 3D node deployment is needed in the Underwater environment. The third important point is locating the sensor node position in 3D deployment because nodes move (Floating Nodes) with water waves. It is a very complex assumption to fix the location of the sensor node.Various locations finding algorithms are proposed for the earthy network. Still, the underwater acoustic communication channel's unique properties, like high and varying transmission delay, required the Algorithm to locate the node's position. Only a few localization algorithms are proposed and presented in recent years to address these location finding requirements. Existing algorithms are distributed, scalable, and iterative in nature, but at the same Time, these algorithms use many acknowledgement messages for location identification and communication. To reduce the number of messages and to overcome the transmission, a new Location Finding and Correcting Algorithm for underwater acoustic sensor networks has been proposed in this paper. Our proposed Algorithm (LCLI- Localization and Correction of Location Information for nodes in UWSNs) find the Location of nodes accurately and efficient by considering localization errors. In this paper, we have also proposed a location correcting Algorithm that may use when the localization errors are more. Our proposed Algorithm (UWSN-LCLI) is compared with existing proposed algorithms, and our Algorithm outperforms and shows significant improvement.

Adaptive Fuzzy Game-Based Energy-Efficient Localization in 3D Underwater Sensor Networks

Numerous applications in 3D underwater sensor networks (UWSNs), such as pollution detection, disaster prevention, animal monitoring, navigation assistance, and submarines tracking, heavily rely on accurate localization techniques. However, due to the limited batteries of sensor nodes and the difficulty for energy harvesting in UWSNs, it is challenging to localize sensor nodes successfully within a short sensor node lifetime in an unspecified underwater environment. Therefore, we propose the Adaptive Energy-Efficient Localization Algorithm (Adaptive EELA) to enable energy-efficient node localization while adapting to the dynamic environment changes. Adaptive EELA takes a fuzzy game-theoretic approach, whereby the Stackelberg game is used to model the interactions among sensor and anchor nodes in UWSNs and employs the adaptive neuro-fuzzy method to set the appropriate utility functions. We prove that a socially optimal Stackelberg–Nash equilibrium is achieved in Adaptive EELA. Through extensive numerical simulations under various environmental scenarios, the evaluation results show that our proposed algorithm accomplishes a significant energy reduction, e.g., 66% lower compared to baselines, while achieving a desired performance level in terms of localization coverage, error, and delay.

A MAC Protocol of Concurrent Scheduling Based on Spatial‐Temporal Uncertainty for Underwater Sensor Networks

Underwater sensor networks (UWSNs) are characterized by large energy consumption, limited power supply, low bit rate, and long propagation delay, as well as spatial‐temporal uncertainty, which present both challenges and opportunities for media access control (MAC) protocol design. The time‐division transmissions can effectively avoid collisions since different nodes transmit packets at different period of time. Nevertheless, in UWSNs with long propagation delay, in order to avoid collisions, the period of time is subject to be long enough, which results in poor channel utilization and low throughput. In view of the long and different propagation delay between a receiving node and multiple sending nodes in UWSNs, as long as there is no collision at the receiving node, multiple sending nodes can transmit packets simultaneously. Therefore, in this paper, we propose a MAC protocol of concurrent scheduling based on spatial‐temporal uncertainty called CSSTU‐MAC (concurrent scheduling based on spatial‐temporal uncertainty MAC) for UWSNs. The CSSTU‐MAC protocol utilizes the characteristics of temporal‐spatial uncertainty as well as long propagation delay in UWSNs to achieve concurrent transmission and collision avoidance. Simulation results show that the CSSTU‐MAC protocol outperforms the existing MAC protocol with time‐division transmissions in terms of average energy consumption and network throughput.

Tracking and Localization based on Multi-angle Vision for Underwater Target

With the cost reduction of underwater sensor network nodes and the increasing demand for underwater detection and monitoring, near-land areas, shallow water areas, lakes and rivers have gradually tended to densely arranged sensor nodes. In order to achieve real-time monitoring, most nodes now have visual sensors instead of acoustic sensors to collect and analyze optical images, mainly because cameras might be more advantageous when it comes to dense underwater sensor networks. In this article, image enhancement, saliency detection, calibration and refraction model calculation are performed on the video streams collected by multiple optical cameras to obtain the track of the dynamic target. This study not only innovatively combines the application of AOD-Net’s (all-in-one network) image defogging algorithm with underwater image enhancement, but also refers to the BASNet (Boundary-Aware Salient network) network architecture, introducing frame difference results in the input to reduce the interference of static targets. Based on the aforementioned technologies, this paper designs a dynamic target tracking system centered on video stream processing in dense underwater networks. As part of the process, most nodes carried underwater cameras. When the dynamic target could be captured by at least two nodes in the network at the same time, the target position could then be calculated and tracked.

SecRET

Node localization is a fundamental requirement in underwater sensor networks (UWSNs) due to the ineptness of GPS and other terrestrial localization techniques in the underwater environment. In any UWSN monitoring application, the sensed information produces a better result when it is tagged with location information. However, the deployed nodes in UWSNs are vulnerable to many attacks, and hence, can be compromised by interested parties to generate incorrect location information. Consequently, using the existing localization schemes, the deployed nodes are unable to autonomously estimate the precise location information. In this regard, similar existing schemes for terrestrial wireless sensor networks are not applicable to UWSNs due to its inherent mobility, limited bandwidth availability, strict energy constraints, and high bit-error rates. In this article, we propose SecRET , a <underline>Sec</underline>ure <underline>R</underline>ange-based localization scheme empowered by <underline>E</underline>vidence <underline>T</underline>heory for UWSNs. With trust-based computations, the proposed scheme, SecRET , enables the unlocalized nodes to select the most reliable set of anchors with low resource consumption. Thus, the proposed scheme is adaptive to many attacks in UWSN environment. NS-3 based performance evaluation indicates that SecRET maintains energy-efficiency of the deployed nodes while ensuring efficient and secure localization, despite the presence of compromised nodes under various attacks.

W-GUN: Whale Optimization for Energy and Delay-Centric Green Underwater Networks.

Underwater sensor networks (UWSNs) have witnessed significant R&D attention in both academia and industry due to their growing application domains, such as border security, freight via sea or river, natural petroleum production and the fishing industry. Considering the deep underwater-oriented access constraints, energy-centric communication for the lifetime maximization of tiny sensor nodes in UWSNs is one of the key research themes in this domain. Existing literature on green UWSNs are majorly adapted from the existing techniques in traditional wireless sensor network relying on geolocation and the quality of service-centric underwater relay node selection, without paying much attention to the dynamic underwater network environments. To this end, this paper presents an adapted whale and wolf optimization-based energy and delay-centric green underwater networking framework (W-GUN). It focuses on exploiting dynamic underwater network characteristics by effectively utilizing underwater whale-centric optimization in relay node selection. Firstly, an underwater relay node optimization model is mathematically derived, focusing on underwater whale dynamics for incorporating realistic underwater characteristics in networking. Secondly, the optimization model is used to develop an adapted whale and grey wolf optimization algorithm for selecting optimal and stable relay nodes for centric underwater communication paths. Thirdly, a complete workflow of the W-GUN framework is presented with an optimization flowchart. The comparative performance evaluation attests to the benefits of the proposed framework and is compared to state-of-the-art techniques considering various metrics related to underwater network environments.

On accurate localization of sensor nodes in underwater sensor networks: a Doppler shift and modified genetic algorithm based localization technique

The problem of localization in under water sensor nodes has led to proposal of many techniques over the past few decades that depend primarily on Time of Arrival and Time Difference of Arrival. While these techniques are intuitively very appealing and easy to deploy, accurate node localization in dynamic under water environment has remained elusive. Sensor nodes deployed underwater tend to move from their original positions due to water currents and hence their exact positions at a given moment of time are not known with precision. Due to inherent drawbacks of radio signal propagation in underwater environment, localization of sensor nodes depends on acoustic signals. In this paper, we propose a Doppler shift based localization followed by a genetic algorithm based optimization technique that improves accuracy in localizing unknown nodes in underwater sensor networks. The proposed technique envisages sink nodes playing a pivotal role in taking over a bulk of the computational load on account of being comparatively more accessible and serviceable as compared to any other nodes in the network that are deployed underwater. The algorithm relies on observed frequency shifts (Doppler shift) of sound waves compared to actual, that happen when source and observer are mobile as they do in a marine environment. While Doppler shift determines the approximate location of an unknown sensor node, genetic algorithm minimizes the error in localization. Our proposed methodology has much lower localization error as compared to existing protocols.

Efficient Node Deployment Algorithm for Enhancing Connectivity and Coverage in Underwater Sensor Networks

As deployment process is one of the major tasks in underwater sensor network due to its constraint like: acoustic communication, energy, processing speed, cost and memory and dynamic nature of water. As many researchers have proposed many algorithms for the deployment of nodes in underwater sensor network. It was always a great issue in WSN as well as underwater sensor networks. This work proposes a node deployment technique based on depth. This work consists the following major components: (i) sensor nodes to sense the phenomena in underwater sensor networks, (ii) multiple surface station on the water surface. Use of multiple surface station provides better area coverage and connectivity in the networks. This work is divided into three phase like: initialization where nodes are randomly deployed at water surface and from 2D network topology, second phase is depth calculation for all the nodes and third is to distribute the depth to each node and send them to their designated depth to expand the 2D network into the 3D network. The proposed technique is simulated on Matlab for the analysis of area coverage and connectivity. Simulation results show better performance in terms of area coverage and connectivity as compared to ADAN-BC.

Topology Control for Energy-Efficient Localization in Mobile Underwater Sensor Networks Using Stackelberg Game

The characteristics of mobile underwater sensor networks (UWSNs), such as low communication bandwidth, large propagation delay, and sparse deployment, pose challenging issues for successful localization of sensor nodes. In addition, sensor nodes in UWSNs are usually powered by batteries whose replacements introduce high cost and complexity. Thus, the critical problem in UWSNs is to enable each sensor node to find enough anchor nodes in order to localize itself, with minimum energy costs. In this paper, an energy-efficient localization algorithm (EELA) is proposed to analyze the decentralized interactions among sensor nodes and anchor nodes. A single-leader-multi-follower Stackelberg game is utilized to formulate the topology control problem of sensor nodes and anchor nodes by exploiting their available communication opportunities. In this game, the sensor node acts as a leader taking into account factors such as “two-hop” anchor nodes and energy consumption, while anchor nodes act as multiple followers, considering their ability to localize sensor nodes and their energy consumption. We prove that both players select best responses and reach a socially optimal Stackelberg-Nash Equilibrium. Simulation results demonstrate that the proposed EELA improves the performance of localization in UWSNs significantly, and in particular, the energy cost of sensor nodes. Compared to the baseline schemes, the energy consumption per node is about 48% lower in EELA, while providing a desirable localization coverage, under reasonable error, and delay.

Autonomous deployment and adjustment of nodes in UWSN to achieve blanket coverage (ADAN-BC)

The efficient deployment of Underwater Sensor Network (UWSN) is prime objective for maximizing the coverage of an area. Further, the deployment of sensors is also signifies the quality of sensed data which is utilized for analysis. In case, nodes are not scattered with an appropriate distance; this will create a large gap/holes in deployment area. Therefore node mobility is one of the solutions proposed for deploying the sensors. However, the main challenge is of increasing the coverage area, maximizing the network lifetime using less energy. In this research paper, the findings of Autonomous Deployment and Adjustment of Nodes in UWSN to achieve Blanket Coverage (ADAC-BC) are presented, where the nodes are uniformly distributed and having mobility. In the initial phase of deployment Mobile Sensor Nodes (MSN) are randomly deployed, thereafter it forms the layers and move to include in clusters for better network coverage as proposed in ADAN-BC algorithm. Cluster information is broadcasted by base station. Performance are evaluated and concluded based on area coverage, energy efficiency, network lifetime and connectivity.

Value of Information Based Data Retrieval in UWSNs.

Sensor nodes in underwater sensor networks may acquire data at a higher rate than their ability to communicate over underwater acoustic channels. Autonomous underwater vehicles may mitigate this mismatch by offloading high volumes of data from the sensor nodes and ferrying them to the sink. Such a mode of data transfer results in high latency. Occasionally, these networks need to report high priority events such as catastrophes or intrusions. In such a scenario the expectation is to have a minimal end-to-end delay for event reporting. Considering this, underwater vehicles should schedule their visits to the sensor nodes in a manner that aids efficient reporting of high-priority events. We propose the use of the Value of Information metric in order to improve the reporting of events in an underwater sensor network. The proposed approach classifies the recorded data in terms of its value and priority. The classified data is transmitted using a combination of acoustic and optical channels. We perform experiments with a binary event model, i.e., we classify the events into high-priority and low-priority events. We explore a couple of different path planning strategies for the autonomous underwater vehicle. Our results show that scheduling visits to sensor nodes, based on algorithms that address the value of information, improves the timely reporting of high priority data and enables the accumulation of larger value of information.

ANN-Based Control of a Multiboat Group for the Deployment of an Underwater Sensor Network

Underwater sensor networks (USNs) can be used for several types of commercial and noncommercial applications. However, some constraints resulting from the nature of aquatic environments severely limit their use. Due to constraints such as large propagation latency, low-bandwidth capacity, and short-distance communications, a large number of USN nodes are deployed to provide reliability in most applications. In this study, an unattended deployment approach based on the use of an autonomous boat group is proposed. A map of the deployment zone and optimal locations of USN nodes are fed into the onboard computers of the boat group. After processing these data and determining paths to be followed, the boat group deploys sensor nodes at predetermined locations. During the deployment, the boat group is controlled by an artificial neural network- (ANN-) based control system for reducing path errors. A set of performance evaluations is given to prove efficiency of the proposed control system. Performance results show that the boat group can successfully follow a predefined path set and deploy USN nodes. The tradeoffs between energy consumptions, end-to-end delay, and number of hops between underwater relay nodes of energy-efficient USN are also examined. The results indicate that increasing the number of hops reduces the total energy consumption and the end-to-end delay.

Micro-ANP Network Protocol Architecture and Simulation Implementation

Due to the unique characteristics of underwater sensor network (UWSN), conventional network protocols for terrestrial WSN are unable to satisfy the performance of UWSN. In addition, the limits of energy, CPU and memory of UWSN nodes demand the protocol stack running on them should be simple and efficient. The paper proposed a Micro-ANP protocol architecture model for UWSN, which are three layered including application layer, network-transport layer and physical layer, optimized packet size using three objective functions: packet throughput, energy consumption and resource consumption under Micro-ANP architecture by means of MATLAB, designed and implemented UWSN simulation platform based on Micro-ANP and QualNet software, lay a solid foundation for further research on underwater sensor network. DOI: http://dx.doi.org/10.11591/telkomnika.v11i4.2328 Full Text: PDF

Mobi-Sync: Efficient Time Synchronization for Mobile Underwater Sensor Networks

Time synchronization is an important requirement for many services provided by distributed networks. A lot of time synchronization protocols have been proposed for terrestrial Wireless Sensor Networks (WSNs). However, none of them can be directly applied to Underwater Sensor Networks (UWSNs). A synchronization algorithm for UWSNs must consider additional factors such as long propagation delays from the use of acoustic communication and sensor node mobility. These unique challenges make the accuracy of synchronization procedures for UWSNs even more critical. Time synchronization solutions specifically designed for UWSNs are needed to satisfy these new requirements. This paper proposes Mobi-Sync, a novel time synchronization scheme for mobile underwater sensor networks. Mobi-Sync distinguishes itself from previous approaches for terrestrial WSN by considering spatial correlation among the mobility patterns of neighboring UWSNs nodes. This enables Mobi-Sync to accurately estimate the long dynamic propagation delays. Simulation results show that Mobi-Sync outperforms existing schemes in both accuracy and energy efficiency.

Enhancing the Reliability of Head Nodes in Underwater Sensor Networks

Underwater environments are quite different from terrestrial environments in terms of the communication media and operating conditions associated with those environments. In underwater sensor networks, the probability of node failure is high because sensor nodes are deployed in harsher environments than ground-based networks. The sensor nodes are surrounded by salt water and moved around by waves and currents. Many studies have focused on underwater communication environments in an effort to improve the data transmission throughput. In this paper, we present a checkpointing scheme for the head nodes to quickly recover from a head node failure. Experimental results show that the proposed scheme enhances the reliability of the networks and makes them more efficient in terms of energy consumption and the recovery latency compared to the previous scheme without checkpointing.

Path unaware layered routing protocol (PULRP) with non‐uniform node distribution for underwater sensor networks

AbstractWe propose path unaware layered routing protocol (PULRP) for 2D underwater sensor networks (UWSNs) with mobile nodes. The steady‐state distribution of mobile nodes in UWSNs is nonuniform in general. Hence, we use a mobility model‐dependent node distribution. The proposed PULRP algorithm consists of two phases. In the first phase (layering phase), a layering structure is presented which is a set of concentric circles, around a sink node. The radii of the concentric circles are chosen based on equal distribution of nodes in every layer. A distributed power control mechanism is also introduced. The power level of nodes in a particular layer is chosen such that communication occurs only with nodes in the next layer. In PULRP, we consider multihop communication from source to sink. Therefore, in the second phase (communication phase), we propose a method to choose the intermediate relay nodes and an on the fly routing algorithm for packet delivery from source node to sink node across the chosen relay nodes. The proposed algorithm, PULRP finds the routing path on the fly and hence, it does not require any fixed routing table, localization, or time synchronization processes. We demonstrate the performance of PULRP using random waypoint (RWP) mobility model in a simulated underwater environment. Our findings show that the proposed algorithm has considerably better throughput (successful packet delivery rate) compared to the underwater diffusion (UWD) algorithm for various node densities as well as node velocities. In addition, the delay performance of PULRP is also better than that of UWD. Copyright © 2008 John Wiley & Sons, Ltd.

UWSim: A Simulator for Underwater Sensor Networks

We present a new simulator for Underwater Sensor Networks (UWSN), named UWSim. Most of the currently available simulators focus greatly on ground-based sensor and ad hoc networks; they do not consider the factors that affect the underwater communication. UWSim, on the other hand, has its focus on handling scenarios specific to UWSN environments. For example, communication between nodes in UWSN must take place at very low frequencies, which a UWSN simulator can achieve. The actual software development was carried out in a purely object-oriented fashion using C# capabilities. The development was highly modularized and was based on object-oriented design methodologies. An illustrative example is provided to show how this simulator can be used to generate useful data characteristic of UWSN environments. Currently, UWSim has support for limited number of functionalities and it calls for further extensions to support a wide range of UWSN simulation exercises.