Dimensionality determination of unknown deployed underwater sensor network (UWSN) using cost function

This paper proposes a novel estimation technique for dimensionality of deployed underwater sensor network (UWSN). In order to obtain the dimension, probing requests are sent from two anchor nodes (i.e., receivers), which are placed inside the network through buoy, to sensor nodes. Then, the sensor nodes transmit Gaussian signal as feedback to the anchor nodes. The cross‐correlation function (CCF) is determined of these Gaussian signals, which varies according to network dimension. As reference, analytical CCF of five reference networks of different dimensions is determined. Thereafter, by comparing the CCFs of unknown and reference UWSN, cost function (CF) is obtained. The lowest value of CF attained by the specific combination of the one reference and the unknown network indicates that the dimension of these networks is identical. The dimension of two unknown deployed networks is investigated to demonstrate the feasibility of the proposed technique. From the illustrated results, it is justified that the new strategy can provide correct information about the dimension of the deployed network.     

The challenges of building mobile underwater wireless networks for aquatic applications

The large-scale mobile underwater wireless sensor network (UWSN) is a novel networking paradigm to explore aqueous environments. However, the characteristics of mobile UWSNs, such as low communication bandwidth, large propagation delay, floating node mobility, and high error probability, are significantly different from ground-based wireless sensor networks. The novel networking paradigm poses interdisciplinary challenges that will require new technological solutions. In particular, in this article we adopt a top-down approach to explore the research challenges in mobile UWSN design. Along the layered protocol stack, we proceed roughly from the top application layer to the bottom physical layer. At each layer, a set of new design intricacies is studied. The conclusion is that building scalable mobile UWSNs is a challenge that must be answered by interdisciplinary efforts of acoustic communications, signal processing, and mobile acoustic network protocol design.     

Fuzzy-based unequal clustering protocol for underwater wireless sensor networks

Underwater wireless sensor network (UWSN) is a network made up of underwater sensor nodes, anchor nodes, surface sink nodes or surface stations, and the offshore sink node. Energy consumption, limited bandwidth, propagation delay, high bit error rate, stability, scalability, and network lifetime are the key challenges related to underwater wireless sensor networks. Clustering is used to mitigate these issues. In this work, fuzzy-based unequal clustering protocol (FBUCP) is proposed that does cluster head selection using fuzzy logic as it can deal with the uncertainties of the harsh atmosphere in the water. Cluster heads are selected using linguistic input variables like distance to the surface sink node, residual energy, and node density and linguistic output variables like cluster head advertisement radius and rank of underwater sensor nodes. Unequal clustering is used to have an unequal size of the cluster which deals with the problem of excess energy usage of the underwater sensor nodes near the surface sink node, called the hot spot problem. Data gathered by the cluster heads are transmitted to the surface sink node using neighboring cluster heads in the direction of the surface sink node. Dijkstra's shortest path algorithm is used for multi-hop and inter-cluster routing. The FBUCP is compared with the LEACH-UWSN, CDBR, and FBCA protocols for underwater wireless sensor networks. A comparative analysis shows that in first node dies, the FBUCP is up to 80% better, has 64.86% more network lifetime, has 91% more number of packets transmitted to the surface sink node, and is up to 58.81% more energy efficient than LEACH-UWSN, CDBR, and FBCA.     

Energy-optimized cluster head selection based on enhanced remora optimization algorithm in underwater wireless sensor network

With the technological advancements, wireless sensor network (WSN) has played an impeccable role in monitoring the underwater applications. Underwater WSN (UWSN) is supported by WSN but subjected to data dissemination in an acoustic medium. Due to challenging conditions in underwater scenario, the limited battery resources of these sensor nodes stem to a crucial research problem that needs to address the energy-efficient routing in UWSN. In this research work, we intend to propose an energy-optimized cluster head (CH) selection based on enhanced remora optimization algorithm (ECERO) in UWSN. Since CH devours the maximum energy among the nodes, we perform selection of CH based on EROA while considering energy, Euclidean distance from sink, node density, network's average energy, acoustic path loss model and lastly, the adaptive quantity of CHs in the network. Further, to reduce the load on CH node, we introduce the concept of sleep scheduling among the closely located cluster nodes. The proposed work improves the performance of recently proposed EOCSR algorithm by great magnitude which claims to mitigate hot-spot problem, but EOCSR still suffers from the same due to relaying a large magnitude of data.     

Signaling game approach to improve the MAC protocol in the underwater wireless sensor networks

Underwater sensor networks (UWSNs) are instructed for critical applications like military surveillance and underwater oil spills that conducted in a very massive three‐dimensional (3‐D) space that needs many underwater nodes (UNs) to cover the target area. Those UNs are not easy to recharge and cannot exploit solar power. MAC protocols deployed for UWSN ought to consider the energy efficiency, so as, to extend the network lifetime with total connectivity and significant throughput. Terrestrial MAC protocols could not be used for UWSN due to long and unpredictable propagation delay. Consequently, the development of a new MAC protocol for the harsh environment as underwater is a challenging task. In this study, we focus on the deployment of TDMA in UWSN for this, two schemes entitled TDMA slot sharing (TSS) and free time slots reallocation (FTSR) are proposed. Received data stored in the buffer waiting for processing and forwarding might lead to an unlimited data transfer latency those results in the buffer overflow. Otherwise, free time slots appearing during the communication process resulting from dead nodes increase uselessly sleep time for the rest of the nodes. Both schemes based on signaling game are proposed to overcome those problems, TSS is used to enable the slot sharing between UNs during the communication process to reduce the buffer overflow. FTSR scheme aims to increase the throughput of UNs by allowing the reuse of free time slots. Numerical results conducted in this work show good improvement in the network performance concerning throughput.     

Hybrid Chameleon Search and Remora Optimization Algorithm-based Dynamic Heterogeneous load balancing clustering protocol for extending the lifetime of wireless sensor networks

Clustering is an indispensable strategy that helps towards the extension of lifetime of each sensor nodes with energy stability in wireless sensor networks (WSNs). This clustering process aids in sustaining energy efficiency and extended network lifetime in sensitive and critical real-life applications that include landslide monitoring and military applications. The dynamic characteristics of WSNs and several cluster configurations introduce challenge in the process of searching an ideal network structure, a herculean challenge. In this paper, Hybrid Chameleon Search and Remora Optimization Algorithm-based Dynamic Clustering Method (HCSROA) is proposed for dynamic optimization of wireless sensor node clusters. It utilized the global searching process of Chameleon Search Algorithm for selecting potential cluster head (CH) selection with balanced trade-off between intensification and extensification. It determines an ideal dynamic network structure based on factors that include quantity of nodes in the neighborhood, distance to sink, predictable energy utilization rate, and residual energy into account during the formulation of fitness function. It specifically achieved sink node mobility through the integration of the local searching capability of Improved Remora Optimization Algorithm for determining the optimal points of deployment over which the packets can be forwarded from the CH of the cluster to the sink node. This proposed HCSROA scheme compared in contrast to standard methods is identified to greatly prolong network lifetime by 29.21% and maintain energy stability by 25.64% in contrast to baseline protocols taken for investigation.     

Energy‐efficient design of 3D UWSNs leveraging compressive sensing and principal component analysis: A communication techniques perspective

The design of energy‐efficient underwater wireless sensor networks (UWSNs) poses many challenges due to the intrinsic properties of propagation medium and limited battery power of sensor nodes. This paper proposes the concept of optimal clustering for three‐dimensional (3D) UWSNs leveraging compressive sensing (CS) and principal component analysis (PCA) technique of data compression. Optimal clustering reduces the energy consumption by selecting the optimal number of clusters whereas CS and PCA compression techniques reduce the energy consumption by considering a lesser number of samples and reduce the data redundancy at cluster heads (CHs) level, respectively. Moreover, three communication techniques like acoustic, electromagnetic (EM), and free‐space optical (FSO) wave are considered for communication in 3D UWSNs. We compared the energy efficiency for all three communication techniques by examining the three base station (BS) positions at the center, at the corner, and at the lateral midpoint of the 3D sensing area. Moreover, performance parameters (network lifetime, throughput, packet drop rate, and latency) are also evaluated for 3D UWSNs. It is observed that PCA outperforms the CS technique. The proposed technique is suitable for long‐term and densely deployed 3D UWSNs, in which saving energy is of crucial importance.     

Distributed estimation of sensors position in underwater wireless sensor network

In this paper, a localisation method for determining the position of fixed sensor nodes in an underwater wireless sensor network (UWSN) is introduced. In this simple and range-free scheme, the node localisation is achieved by utilising an autonomous underwater vehicle (AUV) that transverses through the network deployment area, and that periodically emits a message block via four directional acoustic beams. A message block contains the actual known AUV position as well as a directional dependent marker that allows a node to identify the respective transmit beam. The beams form a fixed angle with the AUV body. If a node passively receives message blocks, it could calculate the arithmetic mean of the coordinates existing in each messages sequence, to find coordinates at two different time instants via two different successive beams. The node position can be derived from the two computed positions of the AUV. The major advantage of the proposed localisation algorithm is that it is silent, which leads to energy efficiency for sensor nodes. The proposed method does not require any synchronisation among the nodes owing to being silent. Simulation results, using MATLAB, demonstrated that the proposed method had better performance than other similar AUV-based localisation methods in terms of the rates of well-localised sensor nodes and positional root mean square error.     

传感器网络的粒子群优化定位算法

无线传感器网络定位问题是一个基于不同距离或路径测量值的优化问题。由于传统的节点定位算法采用最小二乘法求解非线性方程组时很容易受到测距误差的影响,为了提高节点的定位精度,将粒子群优化算法引入到传感器网络定位中,提出了一种传感器网络的粒子群优化定位算法。该算法利用未知节点接收到的锚节点的距离信息,通过迭代方法搜索未知节点位置。仿真结果表明,该算法有效地抑制了测距误差累积对定位精度的影响,提高了节点的定位精度。     

ROTEE: Remora Optimization and Tunicate swarm algorithm-based Energy-Efficient cluster-based routing for EH-enabled heterogeneous WSNs

Since the development of Wireless Sensor Networks (WSNs), the limited battery of the sensor nodes has been an unavoidable concern. Hence, to keep the WSNs operational for a longer possible duration, the recharging of node's battery through harvesting the ambient energy from surroundings (for an example, solar energy) has been proposed. In this work, we focus not only on utilizing the energy harvesting (EH)-enabled sensor nodes for routing purposes but also introduce a novel hybrid optimization ROATSA that uses Remora Optimization Algorithm (ROA) and Tunicate Swarm Algorithm (TSA) for energy-efficient cluster-based routing. The proposed work is termed as ROA and TSA-based Energy-Efficient Cluster-based Routing for EH-enabled WSN (ROTEE). Hybrid ROATSA is chosen due to enhanced convergence and exploitation capabilities. To reduce the financial burden on the network, we use only four EH-enabled nodes and locate them at each periphery of the network, equidistant to each other and the other nodes are 3-level energy heterogeneous sensor nodes. The selection of cluster head (CH) is optimized through ROATSA by considering profile index of each node by evaluating them at energy, distance, load balancing, node density, the delay involved, and network's average energy. The proposed work ROTEE shows supreme performance against the recently proposed clustering techniques.     

Computational intelligence based localization of moving target nodes using single anchor node in wireless sensor networks

Wireless Sensor Networks (WSNs) have tremendous ability to interact and collect data from the physical world. The main challenges for WSNs regarding performance are data computation, prolong lifetime, routing, task scheduling, security, deployment and localization. In recent years, many Computational Intelligence (CI) based solutions for above mentioned challenges have been proposed to accomplish the desired level of performance in WSNs. Application of CI provides independent and robust solutions to ascertain accurate node position (2D/3D) with minimum hardware requirement (position finding device, i.e., GPS enabled device). The localization of static target nodes can be determined more accurately. However, in the case of moving target nodes, accurate position of each node in network is a challenging problem. In this paper, a novel concept of projecting virtual anchor nodes for localizing the moving target node is proposed using applications of Particle Swarm Intelligence, H-Best Particle Swarm Optimization, Biogeography Based Optimization and Firefly Algorithm separately. The proposed algorithms are implemented for range-based, distributed, non-collaborative and isotropic WSNs. Only single anchor node is used as a reference node to localize the moving target node in the network. Once a moving target node comes under the range of a anchor node, six virtual anchor nodes with same range are projected in a circle around the anchor node and two virtual anchor nodes (minimum three anchor nodes are required for 2D position) in surrounding (anchor and respective moving target node) are selected to find the 2D position. The performance based results on experimental mobile sensor network data demonstrate the effectiveness of the proposed algorithms by comparing the performance in terms of the number of nodes localized, localization accuracy and scalability. In proposed algorithms, problem of Line of Sight is minimized due to projection of virtual anchor nodes.     

End-to-End Delay and Energy Efficient Routing Protocol for Underwater Wireless Sensor Networks

Providing better communication and maximising the communication performance in a Underwater Wireless Sensor Network (UWSN) is always challenging due to the volatile characteristics of the underwater environment. Radio signals cannot properly propagate underwater, so there is a need for acoustic technology that can support better data rates and reliable underwater wireless communications. Node mobility, 3-D spaces and horizontal communication links are some critical challenges to the researcher in designing new routing protocols for UWSNs. In this paper, we have proposed a novel routing protocol called Layer by layer Angle-Based Flooding (L2-ABF) to address the issues of continuous node movements, end-to-end delays and energy consumption. In L2-ABF, every node can calculate its flooding angle to forward data packets toward the sinks without using any explicit configuration or location information. The simulation results show that L2-ABF has some advantages over some existing flooding-based techniques and also can easily manage quick routing changes where node movements are frequent.     

水下无线传感器网络中一种安全定位算法

提出一种基于阵列传输结构的无线传感器网络安全定位算法（USA）。该算法主要解决水下无线传感器网络（UWSN）面临的一些安全威胁问题。以提高无线传感器网络安全性,特别是位置信息的安全性为设计目标。利用节点协作形成的阵列作为天线阵列进行相互通信,在不增加额外硬件成本的同时,还获得阵列天线给无线传感器网络带来的优势,如减小多径效应、提高接收端的信噪比、增加系统容量等。USA算法基于这种阵列结构使网络得到很高安全特性,特别是,对Wormhole攻击具有非常好的抵御性能。仿真实验证明该算法的有效性。     

Localization of Wireless Sensor Networks Using a Single Anchor Node

Localization of nodes in a sensor network is essential for the following two reasons: (i) to know the location of a node reporting the occurrence of an event, and (ii) to initiate a prompt action whenever necessary. Different localization techniques have been proposed in the literature. Most of these techniques use three location aware nodes for localization of an unknown node. Moreover, the localization techniques also differ from environment to environment. In this paper, we proposed a localization technique for grid environment. Sensor nodes are deployed in a grid pattern and localization is achieved using a single location aware or anchor node. We have identified three types of node in the proposed scheme: (i) Anchor node, (ii) Unknown node and (iii) Special node. First, the special nodes are localized with respect to the anchor node, then the unknown nodes are localized using trilateration mechanism. We have compared the proposed scheme with an existing localization algorithm for grid deployment called Multiduolateration. The parameters considered for localization are localization time and localization error. It is observed that localization time and error in the proposed scheme is lower than that of Multiduolateration.     

An adaptive target tracking method for 3D underwater wireless sensor networks

Today, underwater target tracking using underwater wireless sensor networks (UWSNs) is an essential part in many military and non-military applications. Most of moving target tracking studies in UWSNs are considered in two-dimensional space. However, most practical applications require to be implemented in three-dimensional space. In this paper an adaptive method based on Kalman filter for moving target tracking in three dimensional space using UWSNs is proposed. Since, energy protection is a vital task in UWSNs; the proposed method reduces the energy consumption of the entire network by a sleep/wake plan. In this plan only 60% of the closer nodes along the path of the moving target will be waked up using a sink activation message and participate in the tracking, while the other nodes remain in sleep state. At each stage of tracking, the location of the target is estimated using a 3D underwater target tracking algorithm with the trilateration method. Subsequently, the estimations and target tracking results are inserted into the Kalman filter as measuring model to produce the final result. Performance evaluation and simulations results indicated that the proposed method improves the average location error by 45%, average estimated velocity by 86%, and average energy consumption by 33% in comparison to the trilateration method. However, computation time is increased as a result of improving tracking accuracy; and tracking accuracy is lost about 20% due to saving energy. It was shown that the proposed method has been able to adaptively achieve a trade-off between tracking accuracy and energy consumption based on real-time user requirements. Such adaption can be controlled trough the sink node based on real-time requirements.     

DRP: An energy‐efficient routing protocol for underwater sensor networks

The features of transmissions in underwater sensor networks (UWSNs) include lower transmission rate, longer delay time, and higher power consumption when compared with terrestrial radio transmissions. The negative effects of transmission collisions deteriorate in such environments. Existing UWSN routing protocols do not consider the transmission collision probability differences resulting from different transmission distances. In this paper, we show that collision probability plays an important role in route selection and propose an energy‐efficient routing protocol (DRP), which considers the distance‐varied collision probability as well as each node's residual energy. Considering these 2 issues, DRP can find a path with high successful transmission rate and high‐residual energy. In fact, DRP can find the path producing the longest network lifetime, which we have confirmed through theoretical analysis. To the best of our knowledge, DRP is the first UWSN routing protocol that uses transmission collision probability as a factor in route selection. Simulation results verify that DRP extends network lifetime, increases network throughput, and reduces end‐to‐end delay when compared with solutions without considering distance‐varied collision probability or residual energy.     

基于运动预测的水下传感器网络MAC协议

 在海洋环境的影响下,水下无线传感器网络(UWSN)节点始终处于运动状态;UWSN采用声信号通信,缓慢的节点移动也会造成UWSN现有的多址接入技术(MAC)协议冲突避免机制失效。该文建立了水下节点的运动模型,基于AR运动预测模型减小水下节点的时空不确定性对于MAC协议的影响,提高发送信息在预约时隙到达的概率。仿真结果表明,采用AR(5)预测可以减小74.8%的时延探测误差。提出了基于预测的预约MAC协议：P-MAC。NS-2仿真结果表明该协议在海浪运动场景下能提高收包成功率(PRR)10%-15%。     

Doppler auxiliary time synchronization algorithm for underwater acoustic sensor network

Time synchronization problem in underwater acoustic sensor networks (UWSN) was studied.Due to the propagation of acoustic signals in underwater environment and nodes movement bring some problems to time synchronization.A distributed time synchronization algorithm was proposed based on Doppler method,called NU-Sync.NU-Sync solved the problem of uncertainty propagation delay caused by nodes movement through calculating relative velocity.And autonomous underwater vehicle (AUV) was used as beacon node which can save energy consumption in the process of calculation clock skew.Simulation resulted show NU-Sync achieves high level time synchronization precision.     

UW‐MAC: An underwater sensor network MAC protocol

As over 70% of the earth's surface is covered by water, it is desirable to deploy underwater sensor networks (UWSNs) to support oceanic research. UWSNs use acoustic waves and are characterized by long and variable propagation delays, intermittent connectivity, limited bandwidth and low bit rates. Energy savings have always been the primary concern in wireless sensor network protocols; however, there are applications where the latency and throughput are prioritized over energy efficiency and are so significant that the application would not be able to satisfy its requirements without them. Although existing duty‐cycle MAC protocols are power efficient, they introduce significant end‐to‐end delivery latency, provide poor throughput and are not suitable for the challenging environment of a UWSN. In this paper, we utilize CDMA as the underlying multiple access technique, due to its resilience to multi‐path and Doppler's effects prevalent in underwater environments. We propose UW‐MAC, a CDMA‐based power‐controlled medium access protocol that uses both transmitter‐based and receiver‐based CDMA inside a formed cluster, and uses a TDMA schedule to make the cluster heads communicate with the base station. Our MAC algorithm targets the latency and throughput needs in addition to its ability to increase the overall network lifetime. We discuss the design of UW‐MAC, and provide a head‐to‐head comparison with other protocols through extensive simulations focusing on the performance in terms of latency, throughput, and energy consumption. Copyright © 2009 John Wiley & Sons, Ltd.     

EMGGR: an energy-efficient multipath grid-based geographic routing protocol for underwater wireless sensor networks

Routing in underwater wireless sensor networks (UWSN) is an important and a challenging activity due to the nature of acoustic channels and to the harsh environment. This paper extends our previous work [Al-Salti et al. in Proceedings of cyber-enabled distributed computing and knowledge discovery (CyberC), Shanghai, pp 331–336, 2014] that proposed a novel multipath grid-based geographical routing (MGGR) protocol for UWSNs. The extended work, EMGGR, viewed the network as logical 3D grids. Routing is performed in a grid-by-grid manner via gateways that use disjoint paths to relay data packets to the sink node. The algorithm consists of three main components: (1) a gateway election algorithm; responsible for electing gateways based on their locations and remaining energy level (2) a mechanism for updating neighboring gateways’ information; allowing sensor nodes to memorize gateways in local and neighboring cells, and (3) a packet forwarding mechanism; in charge of constructing disjoint paths from source cells to destination cells, forwarding packets to the destination and dealing with holes (i.e. cells with no gateways) in the network. The performance of EMGGR has been assessed using Aqua-Sim, which is an NS2 based simulator for UWSNs. Results show that EMGGR is an energy efficient protocol in all simulation setups used in the study. Moreover, EMGGR can also maintain good delivery ratio and end-to-end delay.