Search

Data collection in underwater acoustic sensor networks (UASNs) and the exposure of node location information pose a threat to the security of the entire network. Therefore, the main challenge for underwater acoustic sensor network security is to protect the security and privacy of the node locations. Compared to active attacks, the characteristics of passive attacks are indistinguishable. Therefore, this research focuses on passive attacks in underwater acoustic sensor networks, and an autonomous underwater vehicle (AUV)-aided data-importance-based scheme for protecting location privacy (DIS-PLP) is proposed. The DIS-PLP comprises three main parts. First, the anchor node calculates the importance of the current data based on the historical dataset and decides whether to send data packets to the base station according to the importance result. Subsequently, an AUV privacy violation is defined, and an AUV path planning method is proposed to prevent attackers from tracking the AUV to obtain the location of the source node. Finally, to prevent nodes from waiting too long for AUVs, a secure multi-hop transmission method is proposed that uses fake source nodes to send fake source data packets to hide the real traffic. The simulation results show that the DIS-PLP offers well performance in terms of safety time and delay, which has strong practical significance for Smart Ocean to improve the level of network security. [ABSTRACT FROM AUTHOR]

This article develops a robust global strategy for identifying the linear parameter varying (LPV) errors-in-variables (EIVs) systems subjected to randomly missing observations and outliers. The parameter interpolated LPV autoregressive exogenous model with an uncertain/noisy input is investigated and a nonlinear state-space model is considered for the input generation model (IGM). The parameters estimation of the LPV EIV systems with nonideal observations is realized using the expectation–maximization algorithm which is particular effective for the incomplete data issue. To ensure the robustness in the identification, the Student’s t-distribution which is characterized by its adjustable degree of freedom, is used to handle the measurement non-normality. Since the posterior distributions of the latent states in the IGM are also involved in the identification process and they are difficult to calculate directly, the particle filter is introduced to recursively approximate them instead. Finally, the verification examples are given to demonstrate the effectiveness of the developed strategy. [ABSTRACT FROM AUTHOR]

The Internet of Underwater Things (IoUT) gradually becomes the future direction of ocean. Many devices, which are called the sources, are deployed in the sea to fulfill scientific, civilian, and military needs. If the locations of these sources are leaked, it will cause a serious economic and military crisis. Thus, in this context, the source location privacy protection becomes critical. In this paper, we focus on the source location privacy protection of underwater acoustic sensor networks (UASNs), where a multi-channel interference based source location privacy protection scheme (MCISLP) is proposed. The MCISLP mainly contains four steps. First, to enhance the sense of autonomous underwater vehicles (AUV) for nodes, a noise reduction method is proposed. Then, based on the previous step, an AUV movement prediction method for nodes is presented to ensure the success of packet transmission. After that, for the information exchange among nodes, given the interference of multiple underwater channels, this interference is then utilized to protect the source location privacy. Further, to reduce the channel interference on the source packet, the time slot control is added to weaken the influence. Last, the ant colony algorithm is adopted for the data collection of AUV. The simulation results show that the MCISLP can increase the network safety time by up to 57 $\%$ (compared with data collection algorithms), and balance the energy consumption of nodes (for about 20 $\%$ energy saving), with a minor compromise of energy consumption of AUV and delay. [ABSTRACT FROM AUTHOR]

Submarine pipelines are among the most efficient methods of marine oil transportation, and they are widely used in offshore oil exploitation. However, the complex environment of the ocean and malicious attackers may damage the pipeline. They can be efficiently monitored by deploying a multiplicity of sensor nodes, organized in underwater acoustic sensor networks (UASNs). UASNs is located near oil wells, so that UASNs can sense, broadcast, and receive data surveying the status of the submarine infrastructure timely. Inevitably, UASNs may experience security problems, owing to the open nature of the underwater environment. To address these security issues, this paper proposes a new source location privacy protection scheme based on an offshore oil acquisition platform. In the proposed scheme, the nodes are defined as pipeline and environment locations, and are allocated to different clusters. The concept of forming anonymous clusters by exchanging the identities of a source and a cluster head is introduced to determine fake confounding sources. In addition, a data fragmentation method is devised to reduce the energy consumption resulting from fake packet transmission. Particularly, we propose the deployment of disguised AUVs that collect data from fake sources, as to conceal and protect the location of the actual sources. Simulation results show that the safety time of the network is increased by about 6%. Due to the adoption of the data fragmentation method, the energy consumption of nodes is also decreased. [ABSTRACT FROM AUTHOR]

In recent years, underwater acoustic sensor networks (UASNs) have been widely investigated for ocean environmental monitoring, offshore exploration, and marine military. The core function of UASNs is to collect data for related operations. A number of factors make the monitoring challenging; ocean thermoclines may affect the communication of the underwater nodes and gliders, reducing their communication range at varying depth; moreover, the node movement caused by Ekman drifting effect can significantly interfere with the data transmissions. Thus, these factors are regarded essential towards characterizing the ocean environment. To address these challenges, a sleep-scheduling-based hierarchical data collection algorithm (SSHDCA) for underwater gliders is designed. The UASN is split into multiple virtual cubes, where the nodes in different virtual cubes sleep and work alternately to save energy. Then, the SSHDCA divides the network into a dynamic layer and a static layer. In the dynamic layer, a virtual-cube-based multi-hop method is leveraged to transmit data packets to the central area. In the static layer, an improved density-based clustering technique is applied to assign each node to an appropriate cluster, while the underwater gliders collect data from the cluster heads. Further, to reduce energy consumption, the SSHDCA compresses key and non-key data, reducing the size of the packets. Simulation results have shown that the proposed algorithm is effective in reducing the path length of the gliders and the average energy consumption of the nodes, while increasing the remaining operational life of the whole network. [ABSTRACT FROM AUTHOR]

Intelligent data collection is a key component in underwater acoustic sensor networks, and it plays an important role in seabed environment monitoring, marine resource detection and marine disaster early warning. Owing to the particularities of the underwater environment, such as reduced infrastructure and noisy communication channels, the data collected by underwater nodes are more efficiently transmitted to a control center on the surface by way of an autonomous underwater vehicle (AUV). However, with the increasing complexity of the underwater tasks, using a single AUV for data collection cannot meet the requirements of low latency and low power consumption. To solve this problem, a multi-AUV collaborative data collection algorithm that reduces the load of data collection task on a single AUV is proposed. The algorithm is divided into two stages: multi-AUV task allocation and Q-learning-based AUV path planning. The data transmission of the clusters is regarded as a set of different tasks, which are assigned to the AUVs for completion. Subsequently, path planning is performed to guide the AUVs, so that the tasks are completed promptly and at a reduced cost. Simulation results show that the proposed algorithm can leverage the energy consumption of a network and extend its lifetime. The performance of the proposed algorithm in energy consumption is increased by about 10%, and the delay of data collection is also significantly reduced. [ABSTRACT FROM AUTHOR]

Topology control has drawn considerable attention in underwater wireless sensor networks. With the complexity of the underwater environment considered, the topological model of a three-dimensional dense network is adopted. The partition unit, cluster, and temporary control node are first defined. A clustering dormancy scheduling algorithm is then proposed. Accordingly, a vulnerability repair algorithm is presented with consideration of the vulnerability of sensor nodes to death due to external factors. The failure node, coverage vulnerability, coverage matrix, key position, and supplementary node are defined in the proposed algorithm. The algorithm also uses the coverage matrix and the vulnerability edge nodes to determine whether the overlay vulnerability requires repair. Experimental results indicate that this algorithm is more effective and efficient compared with similar algorithms. [ABSTRACT FROM AUTHOR]

Background: Short interspersed nuclear elements (SINEs) belong to non-long terminal repeat (non-LTR) retrotransposons, which can mobilize dependent on the help of counterpart long interspersed nuclear elements (LINEs). Although 234 SINEs have been identified so far, only 23 are from insect species (SINEbase: http://sines.eimb.ru/). Results: Here, five SINEs were identified from the genome of Plutella xylostella, among which PxSE1, PxSE2 and PxSE3 were tRNA-derived SINEs, PxSE4 and PxSE5 were 5S RNA-derived SINEs. A total of 18 related SINEs were further identified in 13 lepidopteran insects and a baculovirus. The 3′-tail of PxSE5 shares highly identity with that of LINE retrotransposon, PxLINE1. The analysis of relative age distribution profiles revealed that PxSE1 is a relatively young retrotransposon in the genome of P. xylostella and was generated by recent explosive amplification. Integration pattern analysis showed that SINEs in P. xylostella prefer to insert into or accumulate in introns and regions 5 kb downstream of genes. In particular, the PxSE1-like element, SlNPVSE1, in Spodoptera litura nucleopolyhedrovirus II genome is highly identical to SfSE1 in Spodoptera frugiperda, SlittSE1 in Spodoptera littoralis, and SlituSE1 in Spodoptera litura, suggesting the occurrence of horizontal transfer. Conclusions: Lepidopteran insect genomes harbor a diversity of SINEs. The retrotransposition activity and copy number of these SINEs varies considerably between host lineages and SINE lineages. Host-parasite interactions facilitate the horizontal transfer of SINE between baculovirus and its lepidopteran hosts. [ABSTRACT FROM AUTHOR]

In this study, a general network model called multi-progressive image deblurring network is proposed to correct blurring artifacts and local imaging details in underwater images. As a solution to nonuniform image distortion, a deformable convolution module was designed to enrich the encoded information of the image representation. Using a stepwise feature refinement module, multi-progressive image deblurring network can reduce the loss of contextual information to produce a more realistic underwater image for subsequent applications. Constructing a loss function based on multi-scale content can help the model improve image perception quality. We conducted experimental evaluations on large-scale image deblurring benchmark datasets, such as GoPro and HIDE, achieving excellent results with 32.84 dB and 31.03 dB peak signal-to-noise ratio, respectively, using the proposed method. Subsequently, a detailed optimization comparison was conducted on the in-house underwater image deblurring dataset. Multi-progressive image deblurring network obtained higher-quality, clearer images. Compared with the current state-of-the-art image deblurring algorithms, the proposed model achieved significant results with a 6.6% increase in deblur performance in peak signal-to-noise ratio. Finally, we conducted ablation experiments to evaluate the effectiveness of all the modules in the proposed framework. • Multi-progressive structure can hierarchically fuse global context information. • MPDNet outperforms almost all the SOTA methods on the benchmark datasets. • MPDNet is enough lightweight for deblurring tasks on mobile computing platforms. [ABSTRACT FROM AUTHOR]

• The viral infection induced a systemic antiviral response of C. medinalis. • The expression level of oxidative stress related genes of host is significantly changed after infection. • The enhancement of PiggyBac -like transposon activity is related to host immunity. • Inhibition of peroxidation degradation or increase of oxidative stress level may enhance the virulence of baculovirus. Cnaphalocrocis medinalis granulovirus (CnmeGV) is a potential microbial agent against the rice leaffolder. Innate immunity is essential for insects to survive pathogenic infection. Therefore, to clarify the immune response of Cnaphalocrocis medinalis to the viral colonization, the gene expression profile of C. medinalis infected with CnmeGV was constructed by RNA-seq. A total of 8,503 differentially expressed genes (DEGs) were found including 5,304 up-regulated and 3,199 down-regulated unigenes. Gene enrichment analysis indicated that these DEGs were mainly linked to protein synthesis and metabolic process as well as ribosome and virus-infection pathways. Specifically, a significantly up-regulated PiggyBac-like transposon gene was identified suggested that the enhancement of transposon activity is related to host immunity. Further, the DEGs encoding oxidative stress related genes were identified and validated by RT-qPCR. Overall, 9 antioxidant enzyme genes and 4 antioxidant protein genes were up-regulated, and the extensive glutathione S-transferase genes were down-regulated. Our results provide a basis for understanding the molecular mechanisms of baculovirus action and oxidative stress response in C. medinalis and other insects. [ABSTRACT FROM AUTHOR]

All major insecticidal genes of Bacillus thuringiensis var. israelensis (Bti) are controlled by the sporulation-specific sigma factor Sigma E (sigE), while sigE is negatively regulated by Sigma K (sigK). Therefore, knocking out sigK plays an important role in regulating the expression of insecticidal genes in Bti. A sigK deletion mutant of B. thuringiensis var. israelensis strain Bt-59, Bt59(ΔsigK), was constructed by homologous recombination and characterized. The sigK deletion resulted in no mature spores and delayed mother cell lysis from T25 to T60, while the genetically complemented strain, Bt59(HFsigK), had mother cell lysis at T25. Compared to Bt-59, sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) analysis indicated that the expression of Cry4Aa2/4Ba1 and Cyt1Aa1 proteins in Bt59(ΔsigK) increased approximately 1.67 and 1.21 times, respectively. However, there was no significant change in Cry11Aa1 protein expression between the two strains. Bioassay results showed that the sigK deletion mutation slightly reduced the insecticidal activity of Bt-59 against Culex pipiens pallens and did not obviously affect activity against Aedes albopictus. [ABSTRACT FROM AUTHOR]

With the boost of ocean development, the study of UASNs has been gaining much attention from researchers. Nevertheless, UASNs are particularly vulnerable to malicious attacks because of their open and unattended nature. Hence, efficient and reliable security mechanisms are required to maintain the normal operation of UASNs. To defend against sudden network faults and malicious attacks, a novel trust model is proposed. The model is divided into three phases. First, a quantified environment model is developed to reflect the impact of the underwater environment on trust evaluation. Then, a trust update model is constructed based on reinforcement learning to confront hybrid attacks. Finally, a trust redemption model is given to reinstate low trust sensor nodes for improving resource utilization of the network. The experimental results prove that this trust model is effective in achieving highly efficient trust updating in the face of changing attack modes. [ABSTRACT FROM AUTHOR]

SDVN is a promising architecture to extend the computation resources which break through the limitations of current vehicular networks. It is possible to learn new networking schemes by observing the surrounding environment in SDVN. However, within SDVN, the construction and application of such schemes still lack proper consideration in data collection, prediction, verification, and validation before applying these schemes in the real network, which is due to the limited knowledge of the physical environment. Intelligent Digital Twin (IDT) was initially designed for realizing intelligent manufacturing by virtualizing and learning the data of the physical space in cyberspace. Hence, bringing IDT to networking can provide additional valuable functionalities to meet the above considerations by constructing a virtual intelligent network space, aiming to realize the iterative update of the networking schemes in an adaptive way. In this article, we introduce a new network architecture, IDT-SDVN, by maximizing the advantages of SDVNs. We present the challenges and open issues of IDT-SDVNs. A case study is presented to demonstrate the effectiveness of SDVNs. The experimental results show that significant improvement of performance is achieved for vehicular networking with the proposed IDT-SDVNs. [ABSTRACT FROM AUTHOR]

Underwater gliders are being increasingly used for data collection, and the development of methods for optimizing their routes has become a topic of active research. With this aim in mind, in this paper, a complete-coverage path-planning obstacle-avoidance (CCPP-OA) algorithm that ensures avoidance for underwater gliders in sea areas with thermoclines is proposed. First, the entire sea area with the thermocline layer is stratified based on the underwater communication radii of the gliders. Next, the glide angles and initial navigation points of the gliders are determined based on their communication radii at each level to construct the complete-coverage path. Finally, by combining the ant colony algorithm and the determined initial navigation points, the complete-coverage path with obstacle avoidance is planned for the gliders. Simulation results show that the proposed CCPP-OA algorithm enables complete coverage of the entire sea area. Furthermore, the length of the planned path is shorter and the amount of energy consumed is less than that of other algorithms. [ABSTRACT FROM AUTHOR]

Source location privacy (SLP) protection is an important means of security protection in wireless sensor networks (WSNs). With the development of underwater acoustic sensor networks (UASNs), security and privacy have attracted increasing attention. In this study, we incorporated SLP into UASNs as the basis for a novel stratification-based source location privacy (SSLP) scheme. In the SSLP scheme, SLP is protected through the cooperation of autonomous underwater vehicles (AUVs) in each network layer. Because fake source nodes and fake data streams are commonly used in WSNs, methods that have similar functions in UASNs are required. Hence, we incorporate a fake source node into the underwater cluster structure to add randomness to the underwater network. Furthermore, fake data streams have been included within the AUV data collection and transmission for each cluster. Simulation results confirm that the SSLP scheme offers improved security in comparison with existing underwater data transmission schemes. [ABSTRACT FROM AUTHOR]

With the rapid development of intelligent transportation systems, enormous amounts of delay-sensitive vehicular services have been emerging and challenge both the architectures and protocols of vehicular networks. However, existing cloud computing-embedded vehicular networks cannot guarantee timely data processing or service access, due to long propagation delay and traffic congestion at the cloud center. Meanwhile, the current distributed network architecture does not support scalable network management, leading the intelligent data computing policies to be undeployable. With this motivation, we propose to introduce fog computing into vehicular networks and define the Multiple Time-constrained Vehicular applications Scheduling (MTVS) issue. First, to improve the network flexibility and controllability, we introduce a Fog-based Base Station (FBS) and propose a Software-Defined Networking (SDN)-enabled architecture dividing the networks into network, fog, and control layers. To address MTVS issue, instead of normal centralized computing-based approaches, we propose to distribute mobile delay-sensitive task in data-level over multiple FBSs. In particular, we regard the fog layer of SDN-enabled network as an FBS-based network and propose to distribute the computing task based on the FBSs along multiple paths in the fog layer. By Linear Programming, we optimize the optimal data distribution/transmission model by formulating the delay computation model. Then, we propose a hybrid scheduling algorithm including both local scheduling and fog scheduling, which can be deployed on the proposed SDN-enabled vehicular networks. Simulation results demonstrate that our approach performs better than some recent research outcomes, especially in the success rate for addressing MTVS issue. [ABSTRACT FROM AUTHOR]

In this work, we use the acoustic ray model to study passive source localization problems using a single hydrophone for shallow water waveguides. It has been found that conventional matched field processing, which requires a multi-hydrophone array, is no longer effective. In this paper, we introduce matched feature localization to achieve passive source localization using a single hydrophone. The eigenray that contains the arrival structure is the core of the acoustic ray model; however, it is difficult to estimate the relative arrival delay of the eigenray for passive localization, especially in shallow water. Therefore, we propose a novel peak extraction passive source localization method based on the autocorrelation function, which does not require estimation of the relative arrival delay of the eigenray. According to a computer simulation, the proposed method can achieve good performance using only one hydrophone. Further, its performance is validated using wideband data collected on a vertical line array during the Shallow Water 2006 experiment. [ABSTRACT FROM AUTHOR]

Aiming at the problems of the low mobility, low location accuracy, high communication overhead, and high energy consumption of sensor nodes in underwater acoustic sensor networks, the MPL (movement prediction location) algorithm is proposed in this article. The algorithm is divided into two stages: mobile prediction and node location. In the node location phase, a TOA (time of arrival)-based ranging strategy is first proposed to reduce communication overhead and energy consumption. Then, after dimension reduction processing, the grey wolf optimizer (GWO) is used to find the optimal location of the secondary nodes with low location accuracy. Finally, the node location is obtained and the node movement prediction stage is entered. In coastal areas, the tidal phenomenon is the main factor leading to node movement; thus, a more practical node movement model is constructed by combining the tidal model with node stress. Therefore, in the movement prediction stage, the velocity and position of each time point in the prediction window are predicted according to the node movement model, and underwater location is then completed. Finally, the proposed MPL algorithm is simulated and analyzed; the simulation results show that the proposed MPL algorithm has higher localization performance compared with the LSLS, SLMP, and GA-SLMP algorithms. Additionally, the proposed MPL algorithm not only effectively reduces the network communication overhead and energy consumption, but also improves the network location coverage and node location accuracy. [ABSTRACT FROM AUTHOR]

High-quality CPNT is a key technology for deep-sea vehicles that dive into the deep sea and for detecting and developing the deep sea. At present, however, CPNT services for deep-sea vehicles are provided by separate communication, positioning, and navigation systems as well as separate synchronous clocks (atomic clocks). This directly affects the operational efficiency, for example, update rates of up to 0.125 Hz, of deep-sea vehicles engaged in deep-sea scientific research, environmental investigation, and resource development. Therefore, a new design method and operating mode of CPNT is proposed herein to overcome the inherent flaws of the current communication/positioning/navigation modes of deep-sea vehicles; meet the actual demands of deep-sea vehicles in real time; achieve high update rates, low power consumption, and high precision positioning and navigation; and to be combined with the current development trends. The integration of CPNT can both unify time and space references, and reduce the difficulty of multi-sensor information fusion. Thus, the problems of poor navigation and the non-timing functions of deep-sea vehicles can be solved fundamentally. The integration of CPNT will improve the navigation and positioning accuracy as well as the information update rate (up to 1 Hz) of large deep-sea vehicles, such as deepsea human-occupied vehicles, deep-sea remotely operated underwater vehicles, and deep-sea autonomous underwater vehicles. [ABSTRACT FROM AUTHOR]

With the remarkable advances in wireless communications and mobile electronic technologies, traveling users have been demanding continuous and seamless Internet access to enjoy multimedia services such as video streaming, voice over IP, online gaming, and so on, through handheld smart devices. Providing ubiquitous wireless connectivity to mobile users is indispensable to support continuous online services when vehicles move across various kinds of access networks. However, the high vehicle velocity and complex user mobility in the urban environment impose great challenges on designing an efficient mobility management scheme. In this article, we study the packet loss issue in IP mobility support for vehicular networks. We first give detailed descriptions of some major mobility management solutions. Then, we analyze user mobility models in the urban environment and identify the packet loss issue when traveling users roam across various access networks. By flexibly utilizing tunneling and buffering technologies, we correspondingly design a comprehensive solution to eliminate packet loss in each handover scenario of the urban environment. Finally, performance comparisons between the proposed scheme and related proposals have been conducted, which demonstrate a noteworthy potential of the presented scheme in eliminating packet loss and improving handover performance in urban vehicular communications. [ABSTRACT FROM AUTHOR]

The time synchronization in vehicular ad hoc networks (VANETs) has gained significant attention in recent times. In this paper, we focus on the time synchronization in large-scale VANETs and propose an adaptive beacon time synchronization (ABTS) algorithm to enhance timing message synchronization. ABTS algorithm selects the best time synchronization pairs to decrease the number of timing messages transmitted. To guarantee the reliability of synchronization, the clock offset of the connected vehicles periodically readjust to provide a better degree of synchronization accuracy with minimum energy consumption. Based on two-way timing message synchronization, we derive maximum likelihood (ML) estimation and its equivalent Cramer-Rao lower bound (CRLB) for clock offset design in the generalized sender-to-receiver system by assuming a Gaussian noise model. We propose node pair selection algorithms to improve pairwise beacon message timing synchronization. The simulation results validate that our proposed ABTS algorithm performs better than other protocols in terms of synchronization accuracy, the rate of convergence and energy efficiency. [ABSTRACT FROM AUTHOR]

Underwater acoustic sensor networks (UASNs) have been widely applied in underwater scenarios where numerous anchoring or floating sensor nodes collaborate in performing some specific assignments, such as information collection or data transmission. In recent years, the trust model has been known as an important tool in responding to attackers inside the network. Although there are a number of trust models recently been suggested as effective methods for terrestrial networks, it is infeasible to directly apply these trust models in UASNs due to the complex underwater environment and the unreliable underwater acoustic communication. For the purpose of achieving accurate and robust trust evaluation for UASNs, a synergetic trust model based on SVM (STMS) is proposed in this paper. The network is divided into a certain number of interconnected clusters in which cluster heads and cluster members (CMs) are synergetic to perform functions. The STMS is mainly comprised of three parts. In the first part, three kinds of trust evidences, which are refined elaborately to reflect most of the attack results, are generated by CMs. In the second part, the support vector machine (SVM) technology is adopted in training a trust prediction model for evaluating accurate trust value. Furthermore, the mechanism of double cluster heads is presented to improve network security and lifetime in the third part. Simulation results demonstrate that STMS performs better than other related works in the sparse deployment environment, which is reflected in the aspect of detect accuracy of malicious nodes, success rate of communication and network lifetime. [ABSTRACT FROM AUTHOR]

In underwater acoustic sensor networks (UASNs), the sensors are deployed at different areas of the ocean, which perform information collection and delay-sensitive routing to the data center for further processing or industrial computing. However, in UASNs, the network states have spatiotemporal characteristics due to tides or autonomous underwater vehicles. To steadily route the traffic especially when the spatiotemporal characteristics of the UASNs are considered, a network architecture with intelligent traffic engineering or routing policies is indispensable. In this paper, we employ software-defined networking (SDN) technology and propose an SDN-enabled distributed architecture for UASNs. Based on the proposed architecture, we propose a scheme DSR-SDN for delay-sensitive spatiotemporal routing in SDN-enabled UASNs. The DSR-SDN includes three phases: First, topology awareness; second, spatiotemporal characteristics estimation; and third, routing computation. Particularly, with SDN features, DSR-SDN provides topology awareness based on a proposed software-defined beaconing scheme. Based on the detected topology, the spatiotemporal characteristics of the network states are estimated based on a proposed SDN-based hierarchical node localizing approach SDN-HL. Lead by the SDN controllers, SDN-HL makes use of the proposed “minimum weighted gap” formulation and Adam algorithm to optimize the localization and builds the indirect links to increase the localization rate. To route the traffic through the network with spatiotemporal characteristics, we adopt the time-expanded network approach, based on which a spatiotemporal route decision can be made before the routing starts. The simulation results demonstrate that the proposed scheme, i.e., DSR-SDN, can conduct accurate spatiotemporal characteristic estimation for the network states and provide delay-sensitive spatiotemporal routing for the sensed data. [ABSTRACT FROM AUTHOR]

Health is one of the most important considerations for everyone. However, environmental pollution damages people's health seriously, especially those who live in industrial cities. Gas waste, water waste, and waste residue seriously endanger the health of people. Therefore, pollution regulation is one of the keys to improving people's health. In this article, we propose an intelligent pollution monitoring system (PMS) based on the Industrial Internet of Things to prevent direct emission of harmful substances and to build healthier cities. The PMS has three main parts: 1. Real-time pollutant monitoring equipment, which can monitor harmful substances in the gas and water in real time, and further cannot be damaged easily 2. A real-time alarm system, which can send alerts immediately after detecting harmful substances 3. An intelligent and fast response system, which can act to respond to an alarm The experimental results show that the proposed PMS can improve the efficiency of responses to pollution and increase people's health. [ABSTRACT FROM AUTHOR]

The past years have seen a rapid development of autonomous underwater vehicle-aided (AUV-aided) data-gathering schemes in underwater acoustic sensor networks (UASNs). The use of AUVs efficiently reduces energy consumption of sensor nodes. However, all AUV-aided solutions face severe problems in data collection delay, especially in a large-scale network. In this paper, to reduce data collection delay, we propose a prediction-based delay optimization data collection algorithm (PDO-DC). On the contrary to the traditional delay optimization algorithms, Kernel Ridge Regression (KRR) is utilized via cluster member nodes to obtain the corresponding prediction models. Then, the AUV can obtain all cluster data by traversing less cluster head nodes, which can effectively reduce the collection delay of the AUV. The experimental results demonstrate that the proposed method is both feasible and effective. [ABSTRACT FROM AUTHOR]

Constant energy supply for sensor nodes is essential for the development of the green Internet of Things (IoT). Recently, WRSNs have been proposed to resolve the energy limitations of nodes, aiming to realize continuous functioning. In this article, a coverage-aware hierarchical charging algorithm in WRSNs is proposed, considering energy consumption and the degree of node coverage. The algorithm first performs network clustering using the K-means algorithm. In addition, nodes are classified into multiple levels in each cluster to calculate respective anchor points based on the energy consumption rate and coverage degree of nodes. Then, the anchor points converge to an optimized anchor point in each cluster. To reduce charging latency, the optimized anchor points form two disjoint internal and external polygons. Next, mobile chargers travel along the internal and external polygons, respectively. Experimental results indicate that the proposed algorithm can improve charging efficiency and reduce charging latency substantially. [ABSTRACT FROM AUTHOR]

In this paper, an autonomous underwater vehicle (AUV) location prediction (ALP)-based data collection scheme (ALP) has been proposed to overcome high and unbalanced energy consumption for underwater wireless sensor networks. In our scheme, an AUV travels around the network, follows a predefined trajectory, and collects data from the sensor nodes. The nodes near the trajectory send their data to the AUV directly, while the others send data to their neighbors that are closer to the trajectory. To overcome the “hot region” problem, which means the nodes near the trajectory of the AUV consume energy faster and die early, a trajectory adjustment mechanism is applied. A mathematical model is proposed to adjust the trajectory periodically. To guarantee an efficient communication between the nodes and the AUV, a reliable time mechanism is proposed. In this mechanism, only the nodes with a sufficient amount of time are capable to communicate and send their data to the AUV directly. The analyses and simulation results validate that our proposed ALP prolongs the network lifetime and has a higher packet delivery ratio than the existing protocols. [ABSTRACT FROM AUTHOR]

With the recent developments of wireless sensor networks (WSNs), computing and communication have experienced huge advancement. Meanwhile, security has not received the same attention to go along with such developments. In this paper, we focus on the source location privacy problem in WSNs, a hot research topic in security, and propose a probabilistic source location privacy (PSLP) protection scheme for WSNs. A more powerful adversary, which can use hidden Markov model to estimate the state of the source, is considered in this study. To cope with this type of adversary, phantom nodes and fake sources, which are responsible to mimic the behavior of the source, are utilized to diversify the routing path. Then, the weight of each node is calculated as a criterion to select the next-hop candidate. In addition, two transmission modes are designed to transmit real packets. The simulation results demonstrate that the proposed PSLP scheme improves the safety time without compromising the energy consumption. [ABSTRACT FROM AUTHOR]

A space and terrestrial integrated network (STIN) converges satellite communication networks, mobile wireless networking, and the Internet, has greatly extended the scope of cyberspace. The STIN is composed of diverse network elements and supports various access technologies, and the coordinations in the hybrid networks can better support complex and changeable communication tasks. Furthermore, the STIN takes advantage of the merits of low delay and large bandwidth in terrestrial networks, and achieves global coverage without the limitation of geographic conditions, which can support positioning and navigation, emergency relief, space exploration, and so on. However, the research on STIN is still confronted with some fundamental challenges including time-varying network topology, high satellite mobility, large end-to-end delay, scalability, and so on. In this article, we present a composite architecture that integrates space and terrestrial network components for providing anytime anywhere communications by utilizing the software defined networking and mobile edge computing paradigms, which not only facilitates the network management and increases network flexibility, but also provides improved quality of service for global multimedia services. Additionally, we identify a number of challenging issues associated with the proposed STIN architecture, including mobility management, resource management, routing, traffic steering, security, and so on, a [ABSTRACT FROM AUTHOR]

Underwater acoustic sensor networks (UASNs) are widely used in a variety of ocean applications, such as exploring ocean resources or monitoring abnormal ocean environments. However, data collection schemes in UASNs are significantly different from those in wireless sensor networks due to high power consumption, severe propagation delay, and so on. Furthermore, previous research has overlooked practical conditions, such as characteristics of water delamination and energy constraint on autonomous underwater vehicles (AUVs). In this paper, a stratification-based data collection scheme for three-dimensional UASNs is proposed to solve these problems. In this scheme, the network is divided into two layers on the basis of the Ekman drift current model. The upper layer, called the Ekman layer, suffers large water velocity. Thus, nodes in the upper layer will follow the water flow. In this case, we employ a forward set-based multihop forwarding algorithm for data collection. The lower layer suffers small water velocity so that nodes in this layer are considered as relatively static. A neighbor density clustering-based AUV data gathering algorithm is applied in this layer for data collection. By employing different data collection algorithms in different layers, we can integrate the advantages of a multihop transmission scheme and AUV-aided data collection scheme to reduce network consumption and improve network lifetime. The simulation results also confirm the proposed method has good performance. [ABSTRACT FROM AUTHOR]

With the boost of IoT, WSNs have been a well-liked know-how. However, due to WSNs' open and unmonitored nature, security vulnerabilities pose a significant problem. In this article, aiming at SLP, a major security problem, we propose the CASLP protection scheme in WSNs for IoT. To increase the scope of the transmitting path, the source starts the random walk in a given direction. Then, to maintain CASLP convergence, nodes only select their next relay nodes in a specific range. Last, to further improve SLP, we concatenate arcs from several rings around the sink to form a new closed loop. Compared to a ringbased routing scheme, CASLP can reduce delays and energy consumption at the minor expense of safety time in WSNs. [ABSTRACT FROM AUTHOR]

Single-instruction-set architecture (Single-ISA) heterogeneous multi-core processors (HMP) are superior to Symmetric Multi-core processors in performance per watt. They are popular in many aspects of the Internet of Things, including mobile multimedia cloud computing platforms. One Single-ISA HMP integrates both fast out-of-order cores and slow simpler cores, while all cores are sharing the same ISA. The quality of service (QoS) is most important for virtual machine (VM) resource management in multimedia mobile computing, particularly in Single-ISA heterogeneous multi-core cloud computing platforms. Therefore, in this paper, we propose a dynamic cloud resource management (DCRM) policy to improve the QoS in multimedia mobile computing. DCRM dynamically and optimally partitions shared resources according to service or application requirements. Moreover, DCRM combines resource-aware VM allocation to maximize the effectiveness of the heterogeneous multi-core cloud platform. The basic idea for this performance improvement is to balance the shared resource allocations with these resources requirements. The experimental results show that DCRM behaves better in both response time and QoS, thus proving that DCRM is good at shared resource management in mobile media cloud computing. [ABSTRACT FROM AUTHOR]

The emerging real-time and computation-intensive services driven by the Internet of Things, augmented reality, automatic driving, and so on, have tight quality of service and quality of experience requirements, which can hardly be supported by conventional cloud computing. Fog computing, which migrates the features of cloud computing to the network edge, guarantees low latency for location-aware services. However, due to the locality feature of fog computing, maintaining service continuity when mobile users travel across different access networks has become a challenging issue. In this article, we propose a novel software-defined-networking-based fog computing architecture by decoupling mobility control and data forwarding. Under the proposed architecture, we design efficient signaling operations to provide seamless and transparent mobility support to mobile users, and present an efficient route optimization algorithm by considering the performance gain in data communications and system overhead in mobile fog computing. Numerical results from extensive simulations have demonstrated that the proposed scheme can not only guarantee service continuity, but also greatly improve handover performance and achieve high data communication efficiency in mobile fog computing. [ABSTRACT FROM PUBLISHER]

Industrial wireless sensor networks (IWSNs) are an expansion of the Internet of Things paradigm that fully exploits the collective intelligence of smart nodes in industrial processes. The data acquisition of IWSNs in harsh industrial environments is susceptible to transmission failures and time delay while being strict in the performance of reliability and timeliness. This article proposes an SNR-assured anti-jamming clustering routing (SA-AJCR) protocol to address the problem of data transmission in an environment of high ambient noise and complex electromagnetic interference. To ease the influence of the industrial field on wireless communication, the irregular radio range of each node is modeled through field testing, and then its communication range is artificially constrained to ensure that each signal is received under a satisfying SNR. Through mapping out an approximation of jammed areas at the cluster level, SA-AJCR enables IWSNs to be tolerant of node or link failure caused by jamming. Routing paths can be adjusted to greedily bypass the mapped jammed regions in the network without interrupting the data transmission or overriding the CSMA limitation. The simulation results demonstrate that the proposed protocol is effectively able to provide high packet delivery ratio in hostile electromagnetic environments with the existence of jammers. [ABSTRACT FROM AUTHOR]

Smart communities are an emerging communication paradigm that mobilizes physical devices operating in different wireless networks to deliver ubiquitous services. Since wireless communication is vulnerable to physical or link layer jamming, it is essential to map the locations and shapes of jammed regions for adjusting routing policy. However, existing mapping strategies require jammed devices to override the carrier sense multiple access limitation for the declaration of jamming. Besides, the utilization of flat network architectures in existing mapping strategies incurs large communication overhead. In this article, a three-layer hierarchical network structure and a matching top-down mapping mechanism are proposed. Through organizing smart nodes into onehop clusters, the jamming phenomenon can be discovered purely from cluster heads' data reports collected in the sink layer. Each one-hop cluster is also used as a basic mapping unit to identify and measure jammed regions. From cluster-level mapping to sensor-level mapping, jammed areas can be mapped from coarse- to fine-grained. Simulation results demonstrate that the mapping traffic involved in the proposed jammed-area mapping strategy can be reduced substantially. [ABSTRACT FROM PUBLISHER]

Nowadays, mini-drones, officially called unmanned aerial vehicles, are widely used in many military and civilian fields. Compared to traditional ad hoc networks, the mobile ad hoc networks established by UAVs are more efficient in completing complex tasks in harsh environments. However, due to the unique characteristics of UAVs (e.g., high mobility and sparse deployment), existing protocols or algorithms cannot be directly used for UAVs. In this article, we focus on the routes designed for UAVs, and aim to present a somewhat complete survey of the routing protocols. Moreover, the performance of existing routing protocols is compared in detail, which naturally leads to a great number of open research problems that are outlined afterward. [ABSTRACT FROM PUBLISHER]

A space and terrestrial integrated network (STIN) converges satellite communication networks, mobile wireless networking, and the Internet, has greatly extended the scope of cyberspace. The STIN is composed of diverse network elements and supports various access technologies, and the coordinations in the hybrid networks can better support complex and changeable communication tasks. Furthermore, the STIN takes advantage of the merits of low delay and large bandwidth in terrestrial networks, and achieves global coverage without the limitation of geographic conditions, which can support positioning and navigation, emergency relief, space exploration, and so on. However, the research on STIN is still confronted with some fundamental challenges including time-varying network topology, high satellite mobility, large end-to-end delay, scalability, and so on. In this article, we present a composite architecture that integrates space and terrestrial network components for providing anytime anywhere communications by utilizing the software defined networking and mobile edge computing paradigms, which not only facilitates the network management and increases network flexibility, but also provides improved quality of service for global multimedia services. Additionally, we identify a number of challenging issues associated with the proposed STIN architecture, including mobility management, resource management, routing, traffic steering, security, and so on, a [ABSTRACT FROM AUTHOR]

Localization is one of the fundamental issues in Wireless Sensor Networks (WSNs). Recently, various localization methods have been proposed. However, using single anchor node introduces quite long localization delay. Therefore, the path planning problem of a Group of Mobile Anchor Nodes (GMAN) is studied in this paper. First, two path planning schemes named GSCAN and GTURN are proposed. Both GSCAN and GTURN use three mobile anchor nodes which traverse the entire network following the designed trajectory to help nearby unknown nodes with localization. Furthermore, in order to improve localization ratio of unknown nodes, two boundary strategies are proposed to guarantee that the movement trajectories of anchor nodes can cover the whole WSN. Simulation results show that GSCAN and GTURN can achieve better localization performance than LMAT, RPGM and Ou’s in terms of higher localization ratio and lower energy consumption. [ABSTRACT FROM AUTHOR]

In Device-to-Device (D2D) communications of massive Multiple-Input Multiple-Output (MIMO) system, the inter-channel interference (ICI) can severely deteriorate the entire system performance. The beamforming technique can be used to alleviate this situation. Thus the localization of the users' equipment (UE) should be known as a prior. In wireless communication, due to the effect of multipath, the model of incident signal should be regarded as distributed sources instead of point sources. In this paper, we propose a 2-D DOA estimation algorithm for coherently distributed (CD) sources based on conformal array. First, three rational invariance relationships are constructed based on generalized steering vectors (GSVs). Then the propagator method (PM) is used for estimating three rational invariance matrices. Finally, the 2-D DOA of CD sources can be obtained from the eigenvalues of three rational invariance matrices. Without spectrum peaking searching, and estimation and eigendecomposition of sampling covariance matrix, the proposed algorithm has low computational complexity. For the condition with a large amount of data, the distributed and parallel PM is proposed to deal with this problem. Simulation results verify the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

It is essential to accurately diagnose bearing faults to avoid property losses or casualties in the industry caused by motor failures. Recently, the methods of fault diagnosis for bearings using deep learning methods have improved the safety of motor operations in a reliable and intelligent way. However, most of the work is mainly suitable for situations where there is sufficient monitoring data of the bearings. In industrial systems, only a small amount of monitoring data can be collected by the bearing sensors due to the harsh monitoring conditions and the short time of the signals of some special motor bearings. To solve the issue above, this paper introduces a transfer learning strategy by focusing on the multi-local model bearing fault based on small sample fusion. The algorithm mainly includes the following steps: (1) constructing a parallel Bi-LSTM sub-network to extract features from bearing vibration and current signals of industrial motor bearings, serially fusing the extracted vibration and current signal features for fault classification, and using them as a source domain fault diagnosis model; (2) measuring the distribution difference between the source domain bearing data and the target bearing data using the maximum mean difference algorithm; (3) based on the distribution differences between the source domain and the target domain, transferring the network parameters of the source domain fault diagnosis model, fine-tuning the network structure of the source domain fault diagnosis model, and obtaining the target domain fault diagnosis model. A performance evaluation reveals that a higher fault diagnosis accuracy under small sample fusion can be maintained by the proposed method compared to other methods. In addition, the early training time of the fault diagnosis model can be reduced, and its generalization ability can be improved to a great extent. Specifically, the fault diagnosis accuracy can be improved to higher than 80% while the training time can be reduced to 15.3% by using the proposed method. [ABSTRACT FROM AUTHOR]

This study aims to overcome the disadvantages of the original RPL (IPv6 Routing Protocol for Low power and Lossy networks) routing protocol (RPL including problems with energy consumption and energy load balance). We developed a relatively balanced RPL – the improved protocol (IRPL). This protocol is based on an efficient clustering algorithm and an effective topology control model of the loop domain communication route. The clustering algorithm can be used to calculate the optimal number of cluster heads by assumption of the network model. Combined with the clustering probability model and the node competition mechanism, the cluster head node in the wireless sensor network was used to complete the clustering process. In the topology control model, the wireless sensor network was divided into concentric rings with equal areas. Nodes determined the best network route, depending on different levels of ring domain and the optimal forwarding communication area defined in this study. Simulation results indicate that the IRPL routing protocol can reduce overall network energy consumption, balance network energy consumption, and prolong network lifetime. [ABSTRACT FROM AUTHOR]

Nowadays, the study of underwater WSNs (UWSNs) has become a hot topic. However, UWSNs have not been fully utilized in the complex underwater environment, since there are some difficulties in controlling mobile sensor nodes and underwater environment conditions. In addition, how to ensure the security of UWSNs and the safety of underwater mobile sensor nodes has not been solved well. In this article, we study the problem of trust establishment between nodes in UWSNs. We first give a detailed overview of existing trust management mechanisms. Since UWSNs possess specific characteristics, it is noted that those existing mechanisms are not applicable for UWSNs. We then introduce a trust cloud model that is suitable for trust management in UWSNs. [ABSTRACT FROM PUBLISHER]

Mobile crowdsensing is a novel sensing paradigm enabled by the proliferation of mobile devices. Since crowdsensing applications are driven by sufficient users, advanced incentive mechanisms have been designed to enhance users' willingness to participate in sensing tasks. However, incentive mechanisms only provide adequate sensing opportunities on the condition that the available user base is large. If existing users are fewer than the required number of participants, incentive mechanisms will lose efficacy. This article proposes a hybrid framework called HySense to compensate for inadequate sensing opportunities solely provided by incentive mechanisms. Within each sensing cycle, HySense combines mobile devices with static sensor nodes to generate uniformly distributed space-time data under the constraint of field coverage. To balance sensing opportunities among different geographic regions, redundant users are efficiently migrated from densely populated areas to sparsely populated areas. HySense utilizes calibration mode for checking whether the participants' behavior patterns are consistent with the sensing task queue. Therefore, any change caused by unforeseen accidents can be dealt with in advance. [ABSTRACT FROM PUBLISHER]

In a resource-constrained wireless sensor network, energy efficiency is a principle issue for monitoring the movement of continuous objects, such as wild fire and hazardous chemical material. In this paper, a continuous object tracking scheme with two-layer grid model (TGM-COT) is proposed. To address the problem of boundary distortion caused by uneven node distribution, we put forward a novel mechanism for boundary nodes identification. Furthermore, a streamlining mechanism is designed to reduce the amount of uploaded data. Simulation results demonstrate that, without sacrificing additional energy consumption, TGM-COT is able to achieve high tracking accuracy and significantly reduce the communication overhead. [ABSTRACT FROM AUTHOR]

Partial discharge (PD) is the manifestation of insulation degradation, and it is regarded as a great risk in the field of industrial high-voltage insulation system. In this paper, the direction-of-arrival (DOA) estimation algorithm is used for the localization of partial-discharge source. The intersecting point of two rays, which come from two different directions measured by two uniform linear arrays (ULAs), can be regarded as the plane location of partial-discharge source. Fast rise times of partial-discharge pulses result in a wide electromagnetic spectrum, thus this paper focuses on the DOA estimation of wideband signals. The technique of multimodal joint sparse representation (MJSR) has been used to improve the performance of biometrics recognition. Here, we extend it to DOA estimation. The received data are represented by a sparse linear combination of potential steering vectors, while constraining the observations from different frequencies subject to sharing the same sparsity pattern. Based on the simultaneous orthogonal matching pursuit (SOMP) and alternating direction method of multipliers (ADMM), a hard threshold algorithm is proposed for DOA estimation. In order to reduce the computational complexity of hard threshold algorithm, an improved soft threshold DOA estimation algorithm based on the ADMM is proposed as well. The effectiveness of the proposed algorithms is validated by simulations and real tests. [ABSTRACT FROM AUTHOR]

Cnaphalocrocis medinalis is a major pest of rice in South and South-East Asia. Insecticides are the major means farmers use for management. A naturally occurring baculovirus, C. medinalis granulovirus (CnmeGV), has been isolated from the larvae and this has the potential for use as microbial agent. Here, we described the complete genome sequence of CnmeGV and compared it to other baculovirus genomes. The genome of CnmeGV is 112,060 base pairs in length, has a G+C content of 35.2%. It contains 133 putative open reading frames (ORFs) of at least 150 nucleotides. A hundred and one (101) of these ORFs are homologous to other baculovirus genes including 37 baculovirus core genes. Thirty-two (32) ORFs are unique to CnmeGV with no homologues detected in the GeneBank and 53 tandem repeats (TRs) with sequence length from 25 to 551 nt intersperse throughout the genome of CnmeGV. Six (6) homologous regions (hrs) were identified interspersed throughout the genome. Hr2 contains 11 imperfect palindromes and a high content of AT sequence (about 73%). The unique ORF28 contains a coiled-coil region and a zinc finger-like domain of 4–50 residues specialized by two C2C2 zinc finger motifs that putatively bound two atoms of zinc. ORF21 encoding a chit-1 protein suggesting a horizontal gene transfer from alphabaculovirus. The putative protein presents two carbohydrate-binding module family 14 (CBM_14) domains rather than other homologues detected from betabaculovirus that only contains one chit-binding region. Gene synteny maps showed the colinearity of sequenced betabaculovirus. Phylogenetic analysis indicated that CnmeGV grouped in the betabaculovirus, with a close relation to AdorGV. The cladogram obtained in this work grouped the 17 complete GV genomes in one monophyletic clade. CnmeGV represents a new crambidae host-isolated virus species from the genus Betabaculovirus and is most closely relative of AdorGV. The analyses and information derived from this study will provide a better understanding of the pathological symptoms caused by this virus and its potential use as a microbial pesticide. [ABSTRACT FROM AUTHOR]

Recently, underwater wireless sensor networks (UWSNs) have emerged as a promising networking technique for various underwater applications. An energy efficient routing protocol plays a vital role in data transmission and practical applications. However, due to the specific characteristics of UWSNs, such as dynamic structure, narrow bandwidth, rapid energy consumption, and high latency, it is difficult to build routing protocols for UWSNs. In this article we focus on surveying existing routing protocols in UWSNs. First, we classify existing routing protocols into two categories based on a route decision maker. Then the performance of existing routing protocols is compared in detail. Furthermore, future research issues of routing protocols in UWSNs are carefully analyzed. [ABSTRACT FROM PUBLISHER]

Traditional Industrial Wireless Sensor Networks (IWSNs) are constrained by limited battery energy. Recent breakthroughs in wireless power transfer have inspired the emergence of Industrial Wireless Rechargeable Sensor Networks (IWRSNs). IWRSNs usually contain one or more mobile chargers which can traverse the network to replenish energy supply for sensor nodes. The essential problem in mobile energy provisioning is to find the optimum path along which the mobile chargers travel to improve charging performance, prolong the battery lifespan of nodes and reduce the charging latency as much as possible. In this paper, we introduce and analyze the impacts of four traveling paths, namely, SCAN, HILBERT, S-CURVES(ad) and Z-curve on energy provisioning for IWRSNs. This evaluation aims to embody effective and essential properties that a superior traveling path should possess. Our simulations show that S-CURVES(ad) outperforms the other traveling paths in the lifetime of nodes and traveling efficiency. And at the same time, it has relatively small charging latency. [ABSTRACT FROM AUTHOR]

Underwater Acoustic Sensor Networks (UASNs) have drawn great attention for their potential value in ocean monitoring and offshore exploration. In order to make the underwater application possible, the unique characteristics of underwater acoustic channels and continuous node movement inspired the emergence of routing protocols for underwater environment. In this paper, we introduce and compare four prominent routing protocols proposed for UASNs, namely, H2-DAB, GEDAR, E-PULRP, and PER. Performances of the routing protocols are evaluated in terms of the average number of control packets, end-to-end delay, data delivery ratio, and total energy consumption. The impact of water currents on the routing algorithms is also analyzed in our simulation. Experimental results demonstrate that E-PULRP provides high data delivery ratio at the cost of end-to-end delay. H2-DAB has better real-time performance for minimal delay transmission. GEDAR efficiently addresses the problem of void region without introducing extra energy. PER requires the most control packets in the process of routing establishment. Our work aims to provide useful insights to select appropriate routing protocols to fulfil different application requirements in UASNs. [ABSTRACT FROM AUTHOR]