Guangjie Han

• Ph.D
• Professor (Full) at Hohai University

Increasing demands for versatile applications have spurred the rapid development of Unmanned Underwater Vehicle (UUV) networks. Nevertheless, multi-UUV movements exacerbates the spatial-temporal variability, leading to serious intermittent connectivity of underwater acoustic channel. Such phenomena challenge the identification of reliable paths for...

Multi-UAV autonomous cooperative air warfare is an important mode of future intelligent air warfare. However, due to the complexity and uncertainty of air combat situation information, how to accurately interpret the enemy’s sustained combat intent remains a major challenge. To address this problem, we propose a Context-Aware Adaptive Feature Fusio...

The Internet of Underwater Things (IoUT) has garnered significant interest due to its potential applications in monitoring underwater environments. However, the unique characteristics of acoustic communication, such as long propagation delays and high attenuation, present considerable obstacles for achieving efficient and dependable data transmissi...

In underwater acoustic sensor networks (UASNs), source nodes serving as data centers hold significant commercial value and strategic importance, and the leakage of their location information may result in immeasurable negative consequences. Presently, the methods employed to protect the location privacy of source nodes within UASNs face challenges...

Remaining useful life (RUL) prediction of aero-engines is one of the important issues in research related to engine health management. Although deep learning has made great progress in fault diagnosis research, successful training of deep learning models is very time-consuming and difficult to meet the real-time requirements of online RUL predictio...

Mobile Underwater Acoustic Networks (UANs) leverage Autonomous Underwater Vehicles (AUVs) to enhance flexibility and mobility, playing an essential role in ocean research. Similar to static UANs, the Medium Access Control (MAC) protocol is still critical for mobile UANs to achieve efficient communication. However, mobile UANs are delaysensitive and...

Path planning is a basic requirement for Autonomous Underwater Vehicles (AUVs) to accomplish underwater missions. However, previous studies often have limitations, such as ignoring the basic condition that the AUV operates in an ocean current environment and discretizing its actions without considering the action space, which results in the simulat...

With the rapid development of underwater robots, underwater communication techniques, etc., the Autonomous Underwater Vehicle (AUV) cluster network has emerged as a candidate paradigm to perform underwater civil and military applications, e.g., underwater target tracking. In this paper, we focus on how to utilize networking and multi-agent artifici...

Modulation recognition plays a crucial role in the acoustic communication systems of autonomous underwater vehicles (AUVs). However, deploying accurate modulation recognition models on resource-constrained edge devices remains a significant challenge. To address this issue, we propose GIQNet, an endto-end deep-learning framework for underwater acou...

Empowered by the large amounts of sensor data in the Industrial Internet of Things, data-driven fault diagnosis has a pivotal role in improving equipment reliability in harsh industrial environments. To enhance diagnostic performance under unknown operating conditions, transfer learning-based cross-domain fault diagnosis has been emerging. However,...

With the rapid development of the underwater internet of things (UIoT), underwater security challenges, especially the problem of illegal invasion, are becoming increasingly prominent, threatening the security of underwater environments and infrastructures. In this article, we propose an approach combining software defined networking (SDN) and mult...

In the process of data acquisition of underwater acoustic sensor networks (UASNs), the safety of the network is threatened by the disclosure of source node location information. So how to protect the security and privacy of source node location is the main challenge faced by UASN security. To realize this taeget, a hierarchical structure-based algo...

This chapter introduces underwater acoustic noise modeling based on generative-adversarial-network (GAN). In underwater acoustic communications, accurately fitting the impulsive noise is crucial. Traditional models with fixed parameters can only approximate the global heavy-tail distribution of the impulsive noise, failing to capture local distribu...

Confronting the challenge of identifying unknown fault types in rolling bearing fault diagnosis, this study introduces a multi-scale bearing fault diagnosis method based on transfer learning. Initially, a multi-scale feature extraction network, MBDCNet, is constructed. This network, by integrating the features of vibration signals at multiple scale...

Interpretable convolutional neural networks (CNNs) are key to reliable industrial fault diagnosis by elucidating model decision-making processes and extracting high-dimensional data features. Presently, interpretable CNNs include time-frequency transformation methods in convolutional layers, but their hyper-parameter setting (e.g. window size, over...

Semantic segmentation of surface defects is essential to ensure product quality in intelligent manufacturing. However, due to the diversity and complexity of industrial scenarios and defects, existing defect semantic segmentation methods still suffer from inconsistent intraclass and indistinguishable interclass segmentation results. To overcome the...

Underwater acoustic sensor networks (UASNs) provide significant support for marine intelligent transportation system. As an effective security mechanism, the trust prediction model has been gradually deployed in UASNs to detect anomalous attacks and guarantee the security of marine transportation. However, in existing research on trust models for U...

Autonomous Underwater Vehicle (AUV)-assisted Underwater Acoustic Networks (UANs) are promising for complex ocean applications. In essence, an AUV-assisted UAN is still dominated by fixed nodes, and Time Division Multiple Access (TDMA)-based Medium Access Control (MAC) protocols have undisputed practicability in such fixed nodes-dominated UANs since...

Geospatial data is essential for urban planning and environmental sustainability. Utilizing multiple robots, each equipped with 3D LiDAR for remote sensing, to collaboratively construct environmental maps can significantly enhance the efficiency of geospatial data collection. However, efficiently identifying overlapping areas between robots and acc...

The rapid evolution of the Internet of Underwater Things (IoUT) has led to the widespread adoption of autonomous underwater vehicle (AUV)-assisted underwater acoustic sensor networks (UASNs) for various applications such as marine environment monitoring and resource exploration. This article introduces an energy-balanced data collection scheme tail...

With the rapid development of underwater materials technology and underwater robot technology, human exploitation of marine resources has been increasingly advanced, which has given rise to various application scenarios for Autonomous Underwater Vehicle (AUV) cluster networks, such as cooperative data collection and target tracking. In this paper,...

Edge computing is fundamental to filling the various quality-of-service needs for Industrial Internet of Things (IIoT) applications. However, introducing edge computing to IIoT inevitably results in hybrid intrusion problems and fails to satisfy the security demands of IIoT. Fortunately, Lagrange coded computing has emerged as a low-complexity and...

In this study, we address the challenge of traversability analysis for autonomous vehicles in diverse environments, leveraging LiDAR sensors. We propose the Transformer-Voxel-Bird’s eye view (BEV) Network (TVBNet), a novel dual-branch framework designed to increase the accuracy and versatility of such analyses in both urban and off-road conditions....

Recently, the rapid advancement of Multi-Agent Reinforcement Learning (MARL) has introduced a new paradigm for intelligent underwater target tracking within Autonomous Underwater Vehicle (AUV) cluster networks, enabling these networks to intelligently collaborate in target tracking. However, the limited scalability of MARL poses significant challen...

In recent years, autonomous underwater vehicle (AUV) swarms are gradually becoming popular and have been widely promoted in ocean exploration or underwater tracking, etc. In this paper, we propose a multi-AUV cooperative underwater multi-target tracking algorithm especially when the real underwater factors are taken into account. We first give norm...

In the field of deep-sea positioning, this paper aims to enhance accuracy and computational efficiency in positioning calculations. We propose an improved method based on layered clustering of sound velocity profiles, where the profiles are stratified according to maximum distance and maximum density. Subsequently, a secondary curve fitting is appl...

With the increasing popularity of cab services such as Didi and Uber, cities are faced with the challenge of high carbon emissions and traffic congestion. Ride-sharing services, as a novel green mode of transportation, have emerged as a key technology in smart transportation for addressing these problems. The implementation of ride-sharing is predi...

With the wide application of unmanned aerial vehicles (UAVs), performing search and rescue missions autonomously in unknown environment has become an increasingly concerning issue. In this paper, we propose an adaptive conversion speed Q-Learning algorithm (ACSQL). Performing UAV missions autonomously is divided into two stages: rescue mission sear...

As an emerging multi-submersible system, Human Occupied Vehicle (HOV) under a convoy of a set of Autonomous Underwater Vehicles (AUVs) is regarded as the future framework for underwater exploration. In this work, to improve the interoperability and communication efficiency of the multi-submersible formations, we treat the multi-submersible system a...

In order to effectively estimate the depth of the source in the acoustic pressure field, this study investigated the relationship between the distribution of acoustic pressure fields in different adjacent mode groups and the depth of the source in shallow waveguides and proposed a method to estimate the depth of the source on the basis of the adjac...

Underwater acoustic sensor networks (UASNs) are effective instruments for monitoring marine environments and surveying seabed resources, it is important to improve their security protection, including source location privacy protection. Numerous strategies have been presented by researchers to strengthen location privacy, however, the majority of t...

Due to the poisonousness, explosiveness, and diffuseness of some continuous objects (e.g., toxic gas, nuclear radiation, industrial dust), continuous object tracking has a pivotal role in protecting the safety of the people, especially in hazardous industries. To improve production safety, the Industrial Internet of Things (IIoT) has become a promi...

In Mobile Edge Computing (MEC) networks, dynamic service migration can support service continuity and reduce user-perceived delay. However, service migration in MEC networks faces significant challenges due to the uncertainty in future traffic demands, the distributed architecture of MEC networks, high operating costs and the dynamism of network re...

The Internet of Underwater Things (IoUT) has attracted a lot of attention because of its promising applications in underwater environmental monitoring; however, the characteristics of acoustic communication, e.g., long propagation delay and high attenuation, pose great challenges for efficient and reliable underwater data transmission. Currently, o...

Abstract-Due to the harsh deployment environment of the underwater coustic sensor networks (UASNs), a reliable and energy-saving routing algorithm has always been an important challenge and a hot topic. A Non-uniform Clustering (NC) algorithm is designed first in which clusters are genetated according to different node densities. Based on NC, the b...

The position of the source is sensitive and critical information in underwater acoustic sensor networks (UASNs). In this study, a network coding-based scheme called the stratified source location privacy protection scheme (SSLP-NC) with autonomous underwater vehicle (AUV) is suggested for a strong adversary that can decode data. First, for the adve...

Automatically detecting human mental workload to prevent mental diseases is highly important. With the development of information technology, remote detection of mental workload is expected. The development of artificial intelligence and Internet of Things technology will also enable the identification of mental workload remotely based on human phy...

With a growing demand for the development of smart ocean projects, the Internet of Underwater Things (IoUT) integrating multiple networks will gradually become the mainstream, particularly for civil, commercial, and military scenarios. During development, however, the security aspect cannot be ignored. Faced with possible future battles on the ocea...

Underwater vehicles are key carriers for underwater inspection and operation tasks, and the successful implementation of these tasks depends on the positioning and navigation equipment with corresponding accuracy. In practice, multiple positioning and navigation devices are often combined to integrate the advantages of each equipment. Currently, th...

With the booming development of marine exploration technology, new studies such as the oceanix city, smart coastal city, and underwater smart cities have been proposed, and the Internet of Underwater Things (IoUT) has received a lot of attention. Data collection is an important application of the IoUT. The common method is to collect data by traver...

With the rapid development of industrial IoT technology, a growing number of intelligent devices are being deployed in smart factories to digitally upgrade the manufacturing industry. The increasing number of intelligent devices brings a huge task request. Fog computing, which is an emerging distributed computing paradigm, is widely applied to proc...

Ocean exploration is one of the fundamental issues for the sustainable development of human society, which is also the basis for realizing the concept of the Internet of Underwater Things (IoUT) applications, such as the smart ocean city. The collaboration of heterogeneous autonomous marine vehicles (AMVs) based on underwater wireless communication...

The forthcoming 6G networks are expected to provide a vision of overlapping aerial-ground-underwater wireless networks. Meanwhile, the rapid development of the Internet of Underwater Things (IoUTs) brings forth many categories of Autonomous Underwater Vehicle (AUV)-assisted Underwater Wireless Networks (UWNs). In this paper, we argue that the AUV-a...

Accident severity prediction is a hot topic of research aimed at ensuring road safety as well as taking precautionary measures for anticipated future road crashes. In the past decades, both classical statistical methods and machine learning algorithms have been used to predict traffic crash severity. However, most of these models suffer from severa...

In recent years, the industrial motor bearing fault diagnosis method based on deep learning and multi-source information fusion has made some research progress, and research results show that the uncertainty of noise interference and signal measurement error has been improved to a certain extent. However, the multi-source heterogeneous information...

Autonomous underwater vehicles (AUVs)-assisted mobile data collection in underwater wireless sensor networks (UWSNs) has received significant attention because of their mobility and flexibility. To satisfy the increasing demand of diverse application requirements for underwater data collection, such as time-sensitive data freshness, emergency event...

In recent years, cross-domain fault diagnosis problems based on knowledge transfer have attracted considerable attention from researchers, some of whom have adopted domain adaptation algorithms for model transfer under various working conditions. Such algorithms typically assume the samples of the target and source domains share the same fault mode...

Data-driven approaches have gained great success in the field of rotating machinery fault diagnosis for its powerful feature representation capability. However, in most of the current studies, model training process requires massive fault data which is costly to gather or even unavailable in some extreme operating conditions. At the same time, stru...

Underwater image enhancement (UIE) is an essential task for intelligent environment perception in underwater remote visual sensing scenarios. However, the computing power of mobile platforms limits the usage of larger-scale models. In this paper, we propose a lightweight encoder-decoder architecture (UIENet) to enhance underwater images from visual...

Intelligent control of autonomous marine vehicles (AMV) is one of the essential technologies for exploring marine resources. In the deep sea with a complicated exploration environment, collaboration between heterogeneous AMVs can maximize exploration efficiency by utilizing various functional benefits. Accordingly, the paper proposes a method for c...

In industrial Internet of Things, the combination of specific emitter identification (SEI) and key authenticated technologies can effectively resist spoofing attacks and improve system security. However, most existing SEI approaches extract features based on real valued operations and only work in static scenario. This motivated us to develop a nov...

Data collection and transmission is the foundation for Internet of Underwater Things (IoUT) applications. Currently, quite a few Autonomous Underwater Vehicle (AUV)-assisted data collection technologies have been proposed. Most of them concentrate on AUV path planning or multi-path routing for data transmission, although MAC protocol design is cruc...

Performing a high-capacity Medium Access Control (MAC) protocol suffers from low bandwidth and long propagation delay in Underwater Acoustic Networks (UANs). Non-Orthogonal Multiple Access (NOMA) is a promising technology to assist MAC protocols in overcoming the above restrictions and improving UANs’ capacity. It enables multiple users to access t...

Aircraft is an important means of travel and the most convenient and fast vehicle in long-distance transportation. The aircraft engine is one of the most critical parts of an aircraft, and its reliability and safety are extremely important. In this paper, we consider that the operating conditions of aero-engines are complex and changeable, and a mu...

Although semantic segmentation methods have made remarkable progress so far, their long inference process limits their use in practical applications. Recently, some two-branch and three-branch real-time segmentation networks have been proposed to improve segmentation accuracy by adding branches to extract spatial or border information. For the desi...

In the development of Internet of Underwater Things (IoUT), the unknown nature of the underwater environment is a challenging issue. In various domains related to IoUT, utilizing autonomous underwater vehicles (AUVs) for unmanned and autonomous missions has become an inevitable trend. Considering the particularity of underwater environments, this s...

The automatic modulation classification for surface and underwater sensors in the perception layer is crucial in the Internet of Underwater Things (IoUT), where Deep Learning (DL) is becoming an important tool to improve classification accuracy. This work focuses on the radio environment in the perception layer. The biggest challenge in popular DL-...

Even if the big model/big data technologies give a chance that deals with large-scale industrial problems, it has brought a huge demand for computing power. This cannot be provided in most industrial computing scenarios, while low-code and low-cost computing schemes are indispensable, especially on account of the edge computing architecture. This p...

Formation path planning of autonomous underwater vehicles (AUVs) entails establishing optimal collision-free routes over challenging underwater terrain while maintaining state coherence to preserve an intended formation, and path planning techniques have been the subject of significant study over the last decade, with swarm intelligence algorithms...

Unauthorized underwater vehicles (UUVs) pose a serious threat to maritime security. To preserve maritime security, it is essential to pursue these UUVs. The majority of traditional pursuit methods are based on known environmental dynamics. However, the underwater environment is too complicated and unpredictable to describe these dynamics accurately...

Short-term load forecasting is a key digital technology to support urban sustainable development. It can further contribute to the efficient management of the power system. Due to strong volatility of the electricity load in the different stages, the existing models cannot efficiently extract the vital features capturing the change trend of the loa...

Short-term load forecasting (STLF) is essential for urban sustainable development. It can further contribute to the stable operation of the smart grid. With the development of renewable energy, improving STLF accuracy has become a vital task. Nevertheless, most models based on the convolutional neural network (CNN) cannot effectively extract the cr...

Object detection based on point clouds has been widely used for autonomous driving, although how to improve its detection accuracy remains a significant challenge. Foreground points are more critical for 3D object detection than background points; however, most current detection frameworks cannot effectively preserve foreground points. Therefore, t...

With the explosive growth of devices and tasks deployed in the industrial Internet of Things (IIoT), the lack of interconnection and collaboration between devices leads to poor timeliness and security in IIoT resource scheduling. This article focuses on the issue of adaptive scheduling of resources in large-scale IIoT. First, a collaborative termin...

In this paper, we study data transmission in the Terrestrial–Satellite Integrated Network (TSIN), where terrestrial networks and satellites are combined together to provide seamless global network services for ground users. However, efficiency of the data transmission is limited by the time-varying inter-satellite link connection and intermittent t...

It is critical to detect malicious code for the security of the Internet of Things (IoT). Therefore, this work proposes a malicious code detection algorithm based on the novel feature fusion–malware image convolutional neural network (FF-MICNN). This method combines a feature fusion algorithm with deep learning. First, the malicious code is transfo...

With the rapid development of edge intelligence (EI) and machine learning (ML), the applications of Cyber-Physical Systems (CPS) have been discovered in all aspects of the life world. As one of its most essential branches, Medical CPS (MCPS) determines human health and medical treatment in the Internet of Everything (IOE) era. Knowledge sharing is...

Using deep reinforcement learning to solve traffic signal control problems is a research hotspot in the intelligent transportation field. Researchers have recently proposed various solutions based on deep reinforcement learning methods for intelligent transportation problems. However, most signal control optimization takes the maximization of traff...

The Internet of Things (IoT) technology has expanded network space by interconnected devices, which has been widely used in various fields, such as environmental monitoring, object tracking, risk warning, etc. Due to insufficient computing capacity, limited battery life, and unreliable communication environment in IoT, unmanned aerial vehicle (UAV)...

Short-term load forecasting (STLF), especially for regional aggregate load forecasting, is essential in smart grid operation and control. However, the existing CNN-based methods cannot efficiently extract the essential features from the electricity load. The reason is that the basic requirement of using CNNs is space invariance, which is not satisf...

As an effective security mechanism, trust models have been proposed to estimate the reliability of the individual nodes in Underwater Acoustic Sensor Networks (UASNs) during adverse attacks. However, existing trust models neglect the relative importance of the different nodes within the network topology. Further, few trust models study the effects...

In this paper, we develop an edge intelligence based aero-engine performance monitoring system. The proposed approach can effectively predict the remaining useful life of aero-engines, which is the main focus within the prognostics and health management framework – thus it provides support for optimal operation planning and maintenance decisi...

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...

Classical edge computing algorithms assume that the execution time is always known in resource allocation. However, in practice, the execution time in the edge server is hard to estimate due to the complex environment, especially in Internet of Vehicles (IoV), which makes resource allocation a significant challenge. To address this problem, we prop...

With the advancements in Internet of Things (IoT) and communication technologies (5G beyond/6G), Connected and Autonomous Vehicles (CAV) is eventually being realized and will make a major contribution to the development of smart mobility systems in the pursuit of green and sustainable economies. Cooperative driving features allowed by CAVs will dra...

The papers in this special section focus on artificial intelligence (AI)-powered Internet of Everything services in next generation wireless networks. These networks are undergoing a major revolution, connecting billions of machines and millions of people. These networks are marketed as the key enabler of an unprecedented Internet of Everything (Io...

The rapid development of information technology promotes the transformation and development of future air combat, from mechanization to informatization, intelligence, and multiplatform integration. For the multiplatform avionics system in the unmanned aerial vehicle (UAV)-based network, we aim to address the data routing and sharing issues and prop...

Agricultural Internet of Things (IoT) is expected to address several challenges facing the current agriculture industry, including food production, food safety, ecological environment protection, and food waste. However, before achieving this blueprint, a fundamental problem that should be addressed is the sustainability. Unfortunately, solar energ...

The ongoing expansion of the Industrial Internet of Things (IIoT) is enabling the possibility of effective Industry 4.0, where massive sensing devices in heterogeneous environments are connected through dedicated communication protocols. This brings forth new methods and models to fuse the information yielded by the various industrial plant element...

Link prediction is a fundamental research issue in complex network, which can reveal the potential relationships between users. Most of link prediction algorithms are heuristic and based on topology structure. Weisfeiler–Lehman Neural Machine (WLNM), regarded as a new-generation method, has shown promising performance and thus got attention in link...

With the rapid development of edge computing, it has formed a new paradigm for providing the nearest end service close to the data source. However, insufficient supply of resources makes edge computing devices vulnerable to attacks, especially sensitive to resource-consuming attacks. This paper first designs system function module, aiming to deal w...

The papers in this special section focus on artificial intelligence-enabled software defined industrial networks. With the development of intelligent manufacturing, new manufacturing modes such as personalized customization and networked collaboration have been widely developed. These new manufacturing modes require frequent data exchanges between...

Emerging intelligent public transportation systems (IPTS) enable various smart services by collecting sensing data leveraging public transportation. However, existing researches ignore sensors are usually deployed in 3-D space, and a number of generated sensing data are dropped due to limited storage capacities of sensors. To solve the problem, we...

Over recent years, traditional manufacturing factories have been accelerating their transformation and upgrade toward smart factories, which are an important concept within Industry 4.0. As a key communication technology in the industrial internet architecture, time-sensitive networks (TSNs) can break through communication barriers between subsyste...

Performing effective medium access control (MAC) encounters great challenges for mobile underwater acoustic networks (UANs), because it suffers from low signal-to-noise ratio, Doppler shift, large communication latency, and so on. Multi-carrier code-division multiple access (MC-COMA) is a promising modulation technique appropriate for solving the a...

Obstructive sleep apnea (OSA) syndrome is a common sleep disorder and a key cause of cardiovascular and cerebrovascular diseases that seriously affect the lives and health of people. The development of Internet of Medical Things (IoMT) has enabled the remote diagnosis of OSA. The physiological signals of human sleep are sent to the cloud or medical...

Nowadays, with the development of the Internet of Things (IoT), the relationship between sensor manufacturing technology and wireless network communication technology is getting closer. It is a great direction that diagnosing motor fault using the sensors with information perception, data processing, and wireless communication capabilities. To redu...

The trust model has become a promising mechanism to detect anomalous sensor nodes and guarantee security in underwater acoustic sensor networks (UASNs). A trust model is realized by collecting different trust metrics and transforming them into trust values as reliability measurements. However, trust collection and calculation exhibit high latency i...

With the widespread use of industrial Internet technology in intelligent production lines, the number of task requests generated by smart terminals is growing exponentially. Achieving rapid response to these massive tasks becomes crucial. In this paper we focus on the multi-objective task scheduling problem of intelligent production lines and propo...

Transformers have become popular in building end-to-end automatic speech recognition (ASR) systems. However, transformer ASR systems are usually trained to give output sequences in the left-to-right order, disregarding the right-to-left context. Currently, the existing transformer-based ASR systems that employ two decoders for bidirectional decodin...

Accurately estimating the state of equipment plays an important role in ensuring the efficient operation of Industrial 4.0 systems. This paper focuses on monitoring the operating state and detecting the faults of beam pumping units under the condition of heavy noise within the Industrial Internet of Things. On the one hand, the equipment operating...

The paper proposes a novel visual question answering (VQA)-based online teaching effect evaluation model. Based on the text interaction between teacher and students, we give a guide-attention (GA) model to discover the directive clues. Combining the self-attention (SA) models, we reweight the vital feature to locate the critical information on the...

As a prototype of the underwater Internet of Things-enabled maritime transportation systems, multi-Autonomous Underwater Vehicle (AUV)-based Underwater Wireless Networks (UWNs) have become an important research topic due to their distribution and robustness. In this paper, the concept of multi-AUV-based UWNs is first defined, where AUV is regarded...

The exploitation/utilization of marine resources and the rapid development of urbanization along coastal cities result in serious marine pollution, especially underwater diffusion pollution. It is a non-trivial task to detect the source of diffusion pollution, such that the disadvantageous effect of the pollution can be reduced. With the vision of...

The Industrial Internet of Things (IIoT) has been regarded as one of the pillars supporting the conceptual paradigm of the Industry 4.0. Compared with traditional cloud computing schemes, edge computing provides an effective solution towards easing congestion in backhaul links and core networks, while meeting real-time, security and reliability d...

In the emergency rescue scenario where the communication infrastructure is damaged, Unmanned Air Vehicle(UAV) networking communication, as a part of the 6G air-space-ground integrated network system, plays a huge role in the establishment of the emergency communication network. In this paper, we fully consider the distribution of rescue areas, the...

Boundary tracking of sea continuous objects (e.g., oil spills and radioactive waste) is a challenging task that can be tackled via underwater acoustic sensor networks . Existing methods operate by selecting sensor nodes in the proximity of the boundary, and tend to over- or underestimate the actual boundary of the continuous object. In this artic...