Wireless energy transfer (WET) has recently emerged as an appealing solution for power supplying mobile/Internet of Things (IoT) devices. As an enabling WET technology, resonant beam charging (RBC) is well documented for its long-range, high-power, and safe “WiFi-like” mobile power supply. To provide high-quality wireless charging services for multiple users in a given region, we formulate a deployment

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There have been dramatic increases in industrial investment and growing research interests in Internet of Things over the past few years. Driven by the application demand from Internet of everything in the future, the collaboration between traditional cloud and edge cloud is already on the way to provide better service to diverse users. However, due to the high marginal operation and maintenance costs

The Internet of Things (IoT) increases the number of connected devices and supports the ever-growing complexity of applications. Owing to the constrained physical size, the IoT devices can significantly enhance the computational capacity by offloading computation-intensive tasks to the resource-rich edge servers deployed at the base station (BS) via wireless networks. However, how to achieve optimal

With the rapid development of Internet of Things (IoT), mobile crowdsensing (MCS), i.e., outsourcing sensing tasks to mobile devices or vehicles, has been proposed to address the problem of data collection in the scenarios such as smart city. Despite its benefits for a wide range of applications, MCS lacks an efficient incentive mechanism, restricting the development of IoT applications, especially

To satisfy the increasingly complex demands of the Internet of Things (IoT) applications, multiclouds are a promising solution that can provide scalable, various, and abundant resources. However, in multiclouds, each cloud has its specific virtual machine (VM) type and pricing scheme. In addition, the request arrival, network bandwidth, and VM’s price all vary with time and are hardly predicted. In

In this article, we propose an energy-efficiency-aware integrated architecture of cooperative computing (CC) to support the demands of computing amount in the blockchain-based Internet of Things (IoT). Specifically, we assume that multiple computing servers are placed at each data access point (DAP). The computing servers across multiple DAPs can be virtualized to constitute a CC pool to flexibly allocate

JointCloud is a cross-cloud cooperation architecture for integrated Internet service customization. The customized cross-cloud storage service based on this architecture is called JointCloud storage. Storing the Internet of Things (IoT) big data in erasure-coded JointCloud storage systems ensures that data can be accessed when several cloud services interrupt. However, because existing erasure codes

Currently, data sharing for the Internet of Vehicles (IoV) applications has drawn much attention in the framework of developing smart cities and smart transportation. A critical challenge for data sharing is to incentivize users to participate in collecting and sharing data. The traditional incentive mechanism of crowdsourcing is not practical for IoV because of its trust issues. Although blockchain

Nowadays, cloud-supported Internet of Things (Cloud-IoT) has been broadly deployed in smart medical systems, where the limitations of Internet of Things (IoT)-associated medical devices in terms of data access, storage, scalability, and computing are solved through the use of cloud computing architectures. However, with the rapid development of medical equipment and the increasing number of medical

In the era of Internet of Things (IoT), watching videos on mobile devices has been a popular application in our daily life. How to recommend videos to users is one of the most concerned problem for Internet video service providers (IVSPs). In order to provide better recommendation service to users, they deploy cloud servers in a geo-distributed manner. Each server is responsible for analyzing a local

The Internet of Things (IoT) is gradually becoming mature and has already entered our daily life, which interconnects more machines and makes communication more convenient and more intelligent. Massive IoT devices produce innumerable data which need to be analyzed in joint cloud computation (JointCloud) with diversified services. However, due to the weak security of IoT devices, the existing JointCloud

Driven by the tremendous application demands, the Internet of Things (IoT) systems are expected to fulfill computation-intensive and latency-sensitive sensing and computational tasks, which pose a significant challenge for the IoT devices with limited computational ability and battery capacity. To address this problem, edge computing is a promising architecture where the IoT devices can offload their

Network resource allocation is an important issue for designing energy-harvesting wireless sensor networks (EH-WSNs). This article considers the capacity assignment problem in EH-WSNs with the interference channel for fixed data and energy flow topologies. We focus on the optimal data rates, power allocations, and energy transfers, minimizing the total network delay for the network. We first consider

Visitor counting can be attractive to various applications, like business management and marketing investigation. Recently, many studies have employed wireless signals to achieve visitor counting without people’s active participation and privacy intrusion. However, existing systems mainly count the overall visitors inside a certain area, which fails to provide the fine-grained information of the coming

In this article, we present the design and implementation of the software-defined IoT management (SDIM) framework based on software-defined networking (SDN)-enabled architecture that is purposely built for the edge computing multidomain wireless sensor networks (WSNs). This framework can dynamically provision the IoT devices to enable machine-to-machine (M2M) communication as well as continuous operational

The prevalence of the Internet of Things (IoT) and the explosion of available information on the Web have led to an enormous amount of widely available IoT data sets with sparsity. Sparse matrix–vector multiplication (SpMV) is one of the most essential algorithms in various kinds of IoT applications. This article designs an autotuning hybrid computing scheme for SpMV, named ahSpMV, on the powerful

The wireless key generation is a potential way to implement information-theoretically secure key refreshment for the Internet of Things devices. The state-of-the-art work on key generation mainly utilizes the wireless local area network technologies. However, they have not sufficiently considered the typical characteristics of low-power wide-area network (LPWAN), such as lengthy payloads, duty-cycled

This article considers a wireless networked control system (WNCS) consisting of a dynamic system to be controlled (i.e., a plant), a sensor, an actuator, and a remote controller for mission-critical Industrial Internet of Things (IIoT) applications. A WNCS has two types of wireless transmissions, i.e., the sensor’s measurement transmission to the controller and the controller’s command transmission

Magnetic MIMO is a wireless power transfer (WPT) system that employs multiple magnetic resonance coils to provide high efficient wireless power in the near field. Magnetic energy beamforming is a typical scheme to control the currents or voltages of the transmitter coils in order to achieve some objectives. Thus, the magnetic channel information is essential to magnetic beamforming (MagBF), and it

Wireless networked control systems for the Industrial Internet of Things (IIoT) require low-latency communication techniques that are very reliable and resilient. In this article, we investigate a coding-free control method to achieve ultralow latency communications in single-controller-multiplant networked control systems for both slow- and fast-fading channels. We formulate a power allocation problem

Sparse mobile crowdsensing is a practical paradigm for large sensing systems, which recruits a small number of users to sense data from only a few subareas and, then, infers the data of unsensed subareas. In order to provide high-quality sensing services under a budget constraint, we would like to select the most effective users to collect useful sensing data to achieve the highest inference accuracy

In this article, we consider an edge cache-assisted millimeter-wave cloud radio access network (C-RAN). Each remote radio head (RRH) in the C-RAN has a local cache, which can prefetch and store the files requested by the actuators. Multiple RRHs form a cluster to cooperatively serve the actuators, which acquire their required files either from the local caches or from the central processor via multicast

Simultaneous localization and mapping (SLAM) has been extensively researched in past years particularly with regard to range-based or visual-based sensors. Instead of deploying dedicated devices that use visual features, it is more pragmatic to exploit the radio features to achieve this task, due to their ubiquitous nature and the widespread deployment of the Wi-Fi wireless network. This article presents

Massive connectivity is a key requirement for the Internet of Things (IoT). In practice, the network should be capable of accommodating thousands of devices and meeting their traffic demands. In this article, we consider the access phase for IoT in a mixed-analog-to-digital converter distributed massive multiple-input–multiple-output system, in which users are classified into light-load users and heavy-load

Smart cities are based on connected devices generating large quantities of data every instant. These data can be stored at a nearby edge location for initial processing but later sending the data to the backend data centers for storage and further analysis consumes considerable network bandwidth. In this article, we propose a large-scale data migration framework using vehicles. The framework uses a

To enable user diversity and multiplexing gains, a fully digital precoding multiple-input–multiple-output (MIMO) architecture is typically applied. However, a large number of radio frequency (RF) chains make the system unrealistic to low-cost communications. Therefore, a practical three-stage hybrid analog–digital precoding architecture, occupying fewer RF chains, is proposed aiming for a nonorthogonal

Future wireless networks have requirements of large connections, low power consumption, high reliability, and strong security. Considering the abundant available bandwidth of millimeter wave (mmWave) and the large line-of-sight (LOS) link probability of air–ground channel, in this article, we develop a framework to study security, reliability and energy coverage performance of the downlink mmWave simultaneous

In this article, we propose an automatic Wi-Fi fingerprint system that combines an unsupervised dual radio mapping (UDRM) algorithm with the aim of reducing the time-cost needed to acquire Wi-Fi signals. Our proposed system is appropriate for indoor environments and utilizes a minimum description length principle (MDLP)-based radio map feedback (RMF) algorithm that simultaneously optimizes and updates

Low-power wide-area technologies have demonstrated their usefulness in a wide variety of Internet of Things applications. New applications are emerging, requiring a mesh or point-to-point (P2P) topology, in contrast to the conventional star-of-stars topology. In this article, we evaluate the coverage and model the path loss (PL) of these links, based on experimental campaigns in three environments:

Internet of Things (IoT) technology provides the necessary foundation and support for smart city water management. To address the challenge of river pollution prevention and flood control requirements in the urban river system, this article proposes a data-driven model to carry out the optimal operation scheduling of water diversion and drainage pumping stations in the presence of the complex hydrometeorological

In this article, we study an interference management and power allocation problem when electrical power communication (EPC) networks are densely deployed in the coverage of licensed networks. The purpose is to reduce the electricity cost and improve the licensed operator’s profit subject to the quality-of-service (QoS) of licensed users (LUs). First, the electricity cost is modeled based on the Taguchi

The advent of fifth generation (5G) enables the Internet of Things (IoT) to connect a massive number of things. The interaction and communication among these things generate an enormous amount of context-aware data that is semantically diverse. Traditional data representation approaches, such as semantic annotation, ontology, and semantic Web technology are rule based, which lack flexibility and adaptability

Secure data aggregation has been widely studied in the area of the smart grid. Many existing schemes have studied protecting user’s privacy in data aggregation by using advanced cryptographic tools. However, they usually introduce a large computation burden to smart meters in limited computing power or require a trusted authority. How to ensure the efficiency on the user side while preserving user’s

As the Internet of Things (IoT) continues to expand, the need to combine communication technologies to cope with the limitations of one another and to support more diverse requirements will proceed to increase. Consequently, we started to see IoT devices being equipped with multiple radio technologies to connect to different networks over time. However, the detection of the available radio technologies

In this article, we study the pricing and resource management in the Internet of Things (IoT) system with blockchain-as-a-service (BaaS) and mobile-edge computing (MEC). The BaaS model includes the cloud-based server to perform blockchain tasks and the set of peers to collect data from local IoT devices. The MEC model consists of the set of terrestrial and aerial base stations (BSs), i.e., unmanned

Auscultation of heart sounds is a noninvasive and less costly way for congenital heart disease (CHD) diagnosis, especially for pediatric individuals. The deep-learning-based computer-aided heart sound analysis has been widely studied and developed in recent years. In this article, we develop a deep-learning-based computer-aided system for pediatric CHDs diagnosis using two novel lightweight convolution

In blast wave monitoring, a traditional travel time tomography method is encountered with local minimum travel time and low coverage density of rays. In this article, a novel B-spline fitting method with the knot-optimization artificial immune system (AIS) is proposed for 2-D overpressure reconstruction. It possesses the advantages of handling point sets of large sizes and adjusts the knot vector flexibly

With a large number of possible smart objects in Social Internet of Things (SIoT), a recommendation system is of great necessity to help users find smart objects they need. However, traditional recommendation techniques usually exploit user’s rating or feedback information, which are impractical as such kind of user preference information is difficult to collect in the SIoT environment. In addition

Body movement is one of the most important indicators of sleep quality for elderly people living alone. Body movement is crucial for sleep staging and can be combined with other indicators, such as breathing and heart rate to monitor sleep quality. Nevertheless, traditional sleep monitoring methods are inconvenient and may invade users’ privacy. To solve these problems, we propose a contactless body

Mobile-edge computing (MEC) has been witnessed as a promising solution for the vehicular task offloading. Due to the limited computing resource of individual MEC servers, it faces challenges when higher requirements are put forward for timely task processing of a large amount of computations in the emerging vehicular applications. In this article, we strive to realize the efficient vehicular task offloading

In recent years, deep learning (DL) has been successfully and widely applied in the person reidentification (Re-ID). However, the DL-based person Re-ID methods face a bottleneck that the scales of most existing person Re-ID databases are not large enough for training very deep models. To address this problem, a body symmetry and part-locality-guided direct nonparametric deep feature enhancement (DNDFE)

In this article, we consider the satellite Internet of Things (IoT) system, in which the IoT device observes physical processes and transmits the status updates to the monitor node over an error-prone channel with nontrivial propagation delay. The freshness of status updates is characterized by Age of Information (AoI), a novel metric that is defined as the time that elapsed since the freshest received

Unlike most of the upper layer authentication mechanisms, the physical (PHY) layer authentication takes advantages of channel impulse response from wireless propagation to identify transmitted packages with low-resource consumption, and machine learning methods are effective ways to improve its implementation. However, the training of the machine-learning-based PHY-layer authentication requires a large

This article evaluates the quality-of-service performance and scalability of the recently released Bluetooth mesh protocol and provides general guidelines on its use and configuration. Through extensive simulations, we analyze the impact of the configuration of all the different protocol’s parameters on the end-to-end reliability, delay, and scalability. In particular, we focus on the structure of

Edge computing is a promising approach for provisioning distributed cloud services to Internet of Things (IoT) systems. Many recent studies propose that edge nodes use blockchain for the decentralized management and access control of IoT data. However, due to the massive volume of data and related transactions, edge servers will eventually run out of space to store the full chain. We introduce scalable

In most Internet of Things (IoT) deployments, intermediate entities are usually employed for efficiency and scalability reasons. These intermediate proxies break end-to-end security when using even the state-of-the-art transport layer security (TLS) solutions. In this direction, the recent object security for constrained RESTful environments (OSCORE) has been standardized to enable end-to-end security

One of the main challenges in Internet of Things (IoT) is providing communication support to an increasing number of connected devices. In recent years, the narrowband radio technology has emerged to address this situation: narrowband IoT (NB-IoT), which is now part of 5G. Supporting massive connectivity becomes particularly demanding in extreme coverage scenarios, such as underground or deep inside

The ultradense network (UDN) has been identified as a promising technology to address the challenge of the ever increasing demands on data rates or massive accesses, especially for Internet of Things (IoT)-oriented applications. However, the severe co-channel interference (CCI) generated by densely deployed femtocells in UDN poses a critical issue. The conflict graph is widely recognized as an effective

Face authentication systems have gained widespread popularity because of their user-friendly usage and increasing recognition accuracy. Unfortunately, the boom in mobile social networks has bought with it media-based facial forgery; a critical threat where an adversary forges or replays the victim’s photograph/video to fool the system. In this article, we propose EchoFace, an effective and robust liveness

The Internet of Things (IoT), recognized as one of the major technological revolutions in the century, is deployed and used today sociality. The related security issues are taken into account by the academia and industry. Recently, an online/offline certificateless signature scheme (OO-CLS) proposed by Saeed et al. is used to construct a heterogeneous remote anonymous authentication protocol (HRAAP)

In this article, we propose a novel framework of mobile edge computing (MEC)-based hierarchical machine learning (ML) tasks distribution for the Industrial Internet of Things. It is assumed that a batch of ML tasks, such as anomaly detection, need to be executed timely in an MEC setting, where the devices have limited computing capability while the MEC server (MES) has rich computing resources. Thus

With the emerging concept of Wi-Fi radio as sensors, we are witnessing more device-free sensing applications. But we observe that most of the existing works of these applications are meant for simple indoor layout and are not adequate for complex cases, e.g., collapsed structures. In this article, we explore the feasibility of Wi-Fi Halow signals for the collapsed scenario as it can boost rescue efforts

The smart home brings together devices, the cloud, data, and people to make home living more comfortable and safer. Trigger–action programming enables users to connect smart devices using if-this-then-that (IFTTT)-style rules. With the increasing number of devices in smart home systems, multiple running rules that act on actuators in contradictory ways may cause unexpected and unpredictable interference

Long-range radio-frequency wireless charging has received more and more attention in recent years. Unlike the literature that focuses on the mobile charging scenario, which is formulated as a path-planning problem, we consider a static network that consists of a power beacon (PB) and multiple wireless powered user nodes. Each user node is equipped with a rechargeable battery and harvests energy only

In the present evolving world, automobiles have become an intelligent electronic machine and are no longer a mere transport medium. In this article, we attempt to make them smarter by introducing the idea of in-car driver authentication using wireless sensing and develop a system that can recognize drivers automatically. The proposed system can recognize human identity by identifying the unique radio

Featured with high bandwidth, high reliability, and native IP compatibility, WiFi has been recommended for a wide range of Internet-of-Things (IoT) applications. However, WiFi is inherently energy-hungry and it may impose high energy consumption on not only IoT devices but also gateways. To reduce gateway’s WiFi energy consumption, many energy-efficient solutions for WiFi tethering services can be

In this article, we propose a semi-blind full-duplex (FD) amplify-and-forward (AF) relay system with adaptive self-interference (SI) processing assisted by independent component analysis (ICA) for low-latency and high-reliability (LLHR) Internet of Things (IoT). The SI at FD relay is not necessarily canceled as much as possible like the conventional approaches, but is canceled or utilized based on