Comparative Analysis of Magnetic Induction and Optical based Localization for Underwater Wireless Sensor Networks

In the past few decades, optical communication with high data rates up to Gb/s in underwater wireless sensor networks (UWSN) has been extensively investigated. However, now a days researchers are highly focused on proposing/implementing localization algorithms for underwater optical wireless sensor networks (UOWSN) that are both fast in computation and cost efficient in terms of hardware design. In this paper we have used two different setups, one consisting of one led as a transmission node Tx. Where we exploit the effects of different angle on optical communication by implementing Lambert cosine law in a (UOWSN). The second setup is made of a led clutch which can communicate in 360 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sup> . Both setups are used to estimate the location of a sensor node Rx in (UOWSN). To complete the task of localization estimation, a multilateration algorithm based on Euclidean distance between the Tx and Rx nodes is used, where as Gauss–Newton method was used to find the minimum of the function.

Wireless sensor networks (WSNs) are network of physical small sensors which are interconnected through wireless links. WSNs are ubiquitous in diverse types of environment such as air interface and underwater acoustic communication. WSNs are responsible for collecting data, accomplishing appropriate operations on it and if required then relay it to the sink node. WSNs had many issues and challenges specifically in underwater wireless sensor network (UWSN). Secondly there is an issue of network life time as the sensor nodes have limited battery and it is challenging to replace it frequently specially in UWSN. An important challenge in the performance of the DBR is the energy constraint due to limited battery life time, which can cause the entire network to go down. In this paper, we propose an Energy Harvesting Depth Based Routing Protocol (EH-DBR) protocol. Our proposed protocol (EH-DBR) sensor node harvest and store power via external acoustic source in the form of packets. The key advantage of our protocol is that its lifetime will be extended indefinitely. Moreover, our routing protocol can take advantage of DBR architecture without introducing extra cost. We conduct extensive simulations. The results show that EH-DBR can achieve very high packet delivery ratios due to long time performance.

Underwater wireless sensor network (UWSN) has limited bandwidth, long propagation delays, and unrechargeable batteries, which forces the development of techniques minimizing the energy consumption of UWSNs. One solution is clustering that outperforms in terms of energy optimization and, in addition, can also provide scalability and data reliability. The development of clustering algorithms depends on UWSN architectures. In our case, we have proposed a hybrid UWSN network architecture named ACOP-UWSN (ACoustic OPtical Underwater Wireless Sensor Network), which aims for reliable data transmission at the fastest speed with higher data rates and minimized propagation delays. In ACOP-UWSN, optical sensors sense data, whereas acoustic sensors only relay data towards the surface buoy. Clustering of all these nodes may result in unnecessary wastage of the node’s energy and memory. Therefore, we undergo clustering of only optical sensors, as comparatively, sensing and processing of data consume maximum energy and memory than relaying data. In the proposed clustering algorithm, the criteria for cluster head selection are OSNR (optical signal-to-noise ratio) and residual energy. The mathematical derivation of OSNR for underwater wireless optical communication is a key part of the algorithm. The results achieved using the simulation tool show that our proposed OSNR-based energy efficient clustering algorithm (OECA) is efficient in terms of energy and as well data reliability as compared to state of art. The quantitative analysis of the results showed that the total energy consumed for the existing scheme is 450 J, which is more as compared to 400 J of OECA. Similarly, the residual energy of nodes using OECA is 1% greater than the existing scheme. To our knowledge, research on the clustering of optical sensors in UWSN is least available, and we are among the few to work on an OSNR-based clustering algorithm for underwater optical nodes.

Underwater sensor networks are physical networks containing acoustic,magnetic,and static electric field.It has got widely application in ocean data acquisition,pollution forecasting,ocean exploitation,and ocean supervision.And in future it will show its advantages in the battlefield.The state-of-the-art underwater wireless sensor networks are overviewed,and several typical structures of underwater wireless sensor networks are also described.Taking account of the requirements of underwater applications several fundamental key aspects in the design of underwater sensor networks,such as node localization,energy,source localization and other challenges are investigated.Finally open issues in underwater sensor networks are discussed.

Underwater wireless sensor networks nodes deployment optimization problem is studied and underwater wireless sensor nodes deployment determines its capability and lifetime. If no underwater wireless sensor node is available in the monitoring area of underwater wireless sensor networks due to used up energy or any other reasons, the monitoring area where is not detected by any underwater wireless sensor node forms coverage holes. In order to improve the coverage of the underwater wireless sensor networks and prolong the lifetime of the underwater wireless sensor networks, based on the perception model, establish nodes detection model, combining with the data fusion. Because the underwater wireless sensor networks nodes coverage holes appear when the initial randomly deployment, a nodes deployment algorithm based on perception model of underwater wireless sensor networks is designed in this article. The simulation results show that this algorithm can effectively reduce the number of deployment underwater wireless sensor networks nodes, improve the efficiency of underwater wireless sensor networks coverage, reduce the underwater wireless sensor networks nodes energy consumption, prolong the lifetime of the underwater wireless sensor networks.

With the continuous development of marine resources, the position of Underwater Wireless Sensor Network (UWSN) is becoming more and more important, and UWSN needs to know the location of sensor nodes when completing tasks such as marine data collection, environmental monitoring, and aiding navigation, etc. Accurate sensor node location information is the key to effective acquisition of underwater data. The key to effective underwater data acquisition is accurate sensor node location information. Due to the influence of the environment, global positioning system (GPS) signals cannot be propagated underwater, so hydroacoustic communication becomes the best choice for node positioning. However, the unstable underwater environment brings a series of challenges to hydroacoustic communication, such as high channel bit error rate, low bandwidth, large propagation delay, and obvious multipath effect. According to the characteristics and challenges of hydroacoustic communication, this paper classifies the localization algorithms of underwater wireless sensor networks into (i) distance-based and distance-free localization algorithms, (ii) single-hop and multi-hop localization algorithms, and (iii) distributed and centralized localization algorithms.

Water covers more than 70 % of the entire planet, contains much of its natural resources. With the increasing use of underwater sensors for the exploitation and monitoring of vast underwater resources, underwater wireless sensor network (UWSN), mostly based on acoustic transmission technologies, have been developing steadily in terms of operation range and data throughput. In an energy-constrained underwater system environment it is very important to find ways to improve the life expectancy of the sensors. Compared to the sensors of a terrestrial Ad Hoc Wireless Sensor Network (WSN), underwater sensors cannot use solar energy to recharge the batteries, and it is difficult to replace the batteries in the sensors. This paper reviews the research progress made to date in the area of energy consumption in underwater sensor networks (UWSN) and concentrates on developing routing algorithms that support energy efficiency. These algorithms are designed to carry out data communication while prolonging the operation time of WSNs.

Source localization utilizing wireless sensor networks (WSNs) is getting more popular in marine applications because the global positioning system is impractical underwater. Underwater WSNs (UWSNs) necessitate underwater acoustic (UWA) signaling, as opposed to terrestrial WSNs (TWSNs), RSSI-based source localization i.e., Received Signal Strength Indicator is explored in this article. In this paper, we provide an Aqua-Sim simulator, an underwater sensor network simulator built on the NS-3 protocol. Underwater Acoustic Sensor Network and Shadowing approaches are proposed and also a new set of Acoustic data is generated by Shadowing using mathematical calculations. In UWSN, the weighted centroid method is used. We chose RSSI to calculate locations. We were able to improve the accuracy and localization error numbers and mathematical formulae even more by using the modeling approach. Another unique aspect of our approach is that we only employed four anchoring apexes to analyze localization and find the position of the sensor nodes.

Underwater Wireless Sensor Network (UWSN) is a newly emerging wireless technology in which small size sensors with limited energy and limited memory and bandwidth are deployed in deep sea water and various monitoring operations like tactical surveillance, environmental monitoring, and data collection are performed through these tiny sensors. Underwater wireless sensor networks are used for the exploration of underwater resources, oceanographic data collection, flood or disaster prevention, tactical surveillance systems, and unmanned underwater vehicles. Sensor nodes consist of a small memory, a central processing unit, and an antenna. Underwater networks are much different from terrestrial sensor networks as radio waves cannot be used in underwater wireless sensor networks. Acoustic channels are used for communication in deep sea water. Acoustic signals have many limitations, such as limited bandwidth, higher end-to-end delay, network path loss, higher propagation delay, and dynamic topology. Usually, these limitations result in higher energy consumption with a smaller number of packets delivered. The main aim nowadays is to operate sensor nodes having a smaller battery for a longer time in the network. This survey has discussed the state-of-the-art localization based and localization-free routing protocols. Routing associated issues in area of underwater wireless sensor networks have also been discussed.

The Internet of Underwater Things (IoUTs) connects underwater devices to communicate, sense surroundings, and transmit data. Acoustic communication faces bandwidth limitations, making underwater wireless optical communication-free space optics (UWOC-FSO) hybrid systems a promising alternative. However, maintaining sufficient power budget and signal-to-noise ratio (SNR) is a challenging task, making wavelength translation (WT) from visible to infrared (IR) at the water-fiber-air interface crucial for reliable signal transmission. In this paper, we propose an underwater wireless optical communication-single mode fiber-free space optics (UWOC-SMF-FSO) hybrid link based on a photo-detection, remodulate, and forwarding (PRF) relay and intensity modulation-direct detection (IM/DD) scheme for 8 × 1-Gb/s underwater optical wireless sensor network (UWOSN). The PRF relay is installed at a remotely operated underwater vehicle (ROV) to perform WT from visible range to IR. The performance of the sensors is analyzed for different water bodies and weather conditions of underwater and free space optics channels, respectively using metrics of Bit-error rate (BER) and Quality factor (Q-factor) employing Gamma–Gamma channel model. The simulation results show that forward-error correction (FEC) target BER of 10−4 for sensors is achieved under different water bodies and weather conditions. The results obtained from this study show that the proposed UWOC-SMF-FSO hybrid link is flexible, resilient to adverse channel effects, and can be a potential candidate for implementation of high-speed long-distance future IoUTs.

Due to the limited battery power of sensor nodes, design of underwater wireless sensor networks (UWSNs) is very difficult. Information is not gained efficiently through sensor nodes in aquatic environment and energy consumption is also the major problem in UWSNs. We proposed logical sub-region with sink mobility for throughput maximization and energy consumption minimization in rectangular UWSNs (LSSR). Sensor nodes are randomly deployed in the network field. Two mobile sinks are moving strategically in the network field and gather data from their respective nodes and cover the maximum area of the network field. LSSR performs better in terms of network lifetime, throughput and residual energy as shown in the simulation results.

SummaryMobility prediction and fault tolerance are extremely difficult due to underwater characteristics. Energy drain is one of the major causes for node faults. Hence, in this research article, a hybrid optimization algorithm is developed for fault‐tolerant and accurate localization in UWSN. In this technique, Artificial Butterfly Optimization (ABO) algorithm is applied for finding the distance between the anchors and the sensors. Each non‐localized node runs ABO algorithm for finding the distance amid the anchor or beacon nodes. Then, applying Quaternion‐based Backtracking Search Optimization (QBSA) algorithm, non‐localized sensor nodes are localized and to decrease the localization error based on the Received Signal Strength Indicator (RSSI), battery energy, and distance parameters. Aqua‐Sim a tool kit of NS2 is an open‐source software developed for Underwater Wireless Sensor Network research, and this proposed algorithm will be implemented using this software. By simulation results, it is shown that the proposed optimization algorithm reduces the localization error, latency, and cost and energy consumption.

The gradual expansion of the earth's population and the increasing shortage of land resources promote people's exploration of marine resources undoubtedly. Underwater wireless sensor networks (UWSNs) technology has been developed. Its applications involve military field, civil resource detection, scientific research and experiment, etc. The implementation of related applications need to rely on UWSNs node localization, which is one of the key technologies of UWSNs. Accurate node location information is the premise of all applications. Aiming at the low location accuracy and location coverage of existing localization algorithms, a predictive localization algorithm (MGP) based on modified backtracking search optimization (MBSA) and gray wolf optimizer (GWO) for UWSNs is designed in the paper. The whole localization process includes two parts mainly: first floor nodes localization and secondary floor nodes localization. Firstly, MBSA is introduced into the first layer to improve the location accuracy and convergence speed of nodes; Secondly, GWO algorithm is introduced into the secondary layer localization. GWO algorithm optimizes the location information with low estimation accuracy. Finally, the simulation shows that MGP has better localization results than SLMP, MCL-MP and MP-PSO.

Earth is solitary among the rocky planets revolving in the solar system. It is the only planet that is 3/4 covered with oceans of liquid water. In today's era, wireless sensor network is used in almost places and also is an interesting topic for researchers too. But with the advancement in technology, a network similar to wireless sensor network can be deployed under the water with acoustic signals for data transmission. Because of harsh environment and some more challenges, underwater communication becomes tricky. Underwater wireless sensor networks (UWSNs) is an advanced technology for underwater explorations and have demonstrated their quality in underwater applications. UWSN is a blend of wireless technology with sensor technology that has some extraordinary features like smart sensing, intelligent computing, and communication capabilities. Further, to maintain the secure communication underwater, it becomes more and more tricky. This chapter presents an expansive analysis of challenges, attacks, and security techniques of UWSNs.

Packet collision in underwater wireless sensor networks (UWSNs) can create inconsistent time stamps leading to inaccurate time synchronization in underwater sensor networks. Most extant time synchronization techniques do not model for the probability of packet collision in UWSNs. This paper proposes a novel non-homogenous Poisson process (NHPP)-based back-off technique that estimates probability of packet collision in UWSN over a set period of time and allows sending of data packets only when probability of collision in a network is low. Any inconsistent time stamps are further identified and removed using Mahalanobis distance technique before linear regression is run. The proposed method performs better in extensive simulations as compared to two similar time synchronization techniques in literature.KeywordsUWSNsNon-homogenous Poisson processPacket collisionTime synchronization