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More than half of the world’s current population resides in urban areas to compare to just 30% in the 1950s. The process of urbanization leads to exurban sprawl, the formation of slums, scattered workplaces, and aging infrastructure. These may cause huge inefficiencies in energy use, traffic, governance, waste management, and pollution, among others. To overcome these social, economic, and environmental

The spectrum access system (SAS) is being deployed as a key component of the emerging spectrum sharing paradigm to address the spectrum crunch facing the U.S. wireless industry. Ensuring security and privacy of this system against potential attacks is a task of paramount importance. In this article, we first introduce the SAS system, describing its three-tier access model, its functional architecture

The fast-growing Internet-of-Things (IoT) market has opened up a large threat landscape, given the wide deployment of IoT devices in both consumer and commercial spaces. Attacks on IoT devices generally consist of multiple stages and are dispersed spatially and temporally. These characteristics make it challenging to detect and identify the attack stages using solutions that tend to be localized in

Cross-Technology Communication (CTC) is an emerging technique that enables direct communication across different wireless technologies. The state-of-the-art works in this area propose physical-level CTC, in which the transmitters emulate signals that follow the receiver’s standard. Physical-level CTC means considerable processing complexity at the transmitter, which does not apply to the communication

The Internet-of-Things (IoT) platform is faced with critical challenges posed by the conflict between resource-hungry IoT applications and resource-constrained IoT devices. Mobile-edge computing provides a promising solution by allowing IoT devices to offload their computation to nearby edge servers to enable fast and energy-efficient data processing. In this article, we study a scenario, where two

Recent applications of the Internet of Things and cyber–physical systems require the integration of many sensing and control tasks into resource-constrained embedded devices. Such tasks can often tolerate a bounded number of timing violations. The concept of weakly hard real-time systems can effectively improve resource efficiency without sacrificing system safety. However, the existing studies have

This study presents a novel nonuniform power formation algorithm (NUPFA) for Bluetooth low-energy (BLE) networks. With two stages, NUPFA constructs the scatternet in a distributed manner. In the first stage, the master and slave nodes discover each other using low-level power to form an initial scatternet. In the second stage, each master alternatively scans or advertises using normal power to interconnect

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Driven by the Internet-of-Things (IoT)-enabled massively data-intensive applications, such as virtual-augmented-reality-based gaming, ultramassive machine-type communications, holographic rendering and high-precision communications, multiway teleconferencing, etc., there is a need for technological advancements and evolutions for wireless communications beyond the fifth-generation (5G) networks. The

Large intelligent surface (LIS) has recently emerged as a potential enabling technology for 6G networks, offering extended coverage and enhanced energy and spectral efficiency. In this work, motivated by its promising potentials, we investigate the error rate performance of LIS-assisted nonorthogonal multiple access (NOMA) networks. Specifically, we consider a downlink NOMA system, in which data transmission

Network coding is an elegant and novel technique to improve network throughput and performance. It is considered as a critical technology to facilitate ever-increasing demands of future wireless networks. It exploits the broadcast nature of wireless media and cooperatively codes packets from different senders to provide reliable, secure, and efficient transmissions. Current research focuses on either

As a result of the increasing deployment of Industrial-Internet-of-Things (IIoT) architectures, large volumes of multidimensional data are continuously generated. An important issue with these data is that higher dimensionality increases the degree of fragmentation. Furthermore, data sets collected by IIoT nodes often display outliers, which are usually caused by anomalous events or errors. These outliers

Space–air–ground-integrated power Internet of Things (SAG-PIoT) can provide ubiquitous communication and computing services for PIoT devices deployed in remote areas. In SAG-PIoT, the tasks can be either processed locally by PIoT devices, offloaded to edge servers through unmanned aerial vehicles (UAVs), or offloaded to cloud servers through satellites. However, the joint optimization of task offloading

Big data, including applications with high security requirements, are often collected and stored on multiple heterogeneous devices, such as mobile devices, drones, and vehicles. Due to the limitations of communication costs and security requirements, it is of paramount importance to analyze information in a decentralized manner instead of aggregating data to a fusion center. To train large-scale machine

The purposes are to enable large-scale Internet of Things (IoT) devices to analyze data more effectively and provide high-efficiency, low-energy, and wide-coverage technical services for terminals. The channel model and energy loss model analyze the devices’ access performance, data transmission path delay, energy consumption in the IoT, and large-scale devices’ access in the cellular narrowband IoT

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This article presents a smart bandage with wireless strain and temperature sensors and a batteryless near-field communication (NFC) tag. Both sensors are based on conductive poly (3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) polymer. The highly sensitive strain sensor consists of a microfluidic channel filled with PEDOT:PSS in Polydimethylsiloxane (PDMS) substrate. The strain sensor

The ever-increasing number of devices on wearable and portable systems comes with challenges such as integration complexity, higher power requirements, and less user comfort. In this regard, the development of multifunctional devices could help immensely as they will provide the same functionalities with lesser number of devices. Herein, we present a dual-function flexible loop antenna printed on polyvinyl

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AI/machine learning has demonstrated significant success in transforming massive and complex data sets into highly accurate knowledge as outcomes, greatly facilitating analysis, intelligence, decision making, and automation across a number of diverse systems. Through integration with advances in data processing, computing, and networking technologies, AI/machine learning is capable of providing a viable

Industry 4.0 is a promising evolution in the field of smart farming by improving the productivity and reducing human intervention to modernize agriculture. This smart paradigm incorporates different levels of the automation from cropping to production yield through sophisticated techniques. Different intelligent computing techniques and communication technologies are augmented with the industry paradigm

Currently, connected vehicles have gradually stepped into our daily lives, and they generally rely on vehicular networks to generate and exchange traffic-related messages to improve the overall travel safety and efficiency. However, due to the open nature of vehicular networks, these traffic-related messages could be erroneous, which may be caused by various reasons, ranging from an onboard device

Currently, developments in wireless sensing technologies have shown that wireless signals can be employed to transmit information between wireless communication devices and are also able to realize passive target wireless sensing. Wireless sensing has diverse Internet-of-Things applications in indoor human detection, such as in device-free localization, activity recognition and fall detection, respiration

The Internet of Things (IoT) provides applications and services that would otherwise not be possible. However, the open nature of IoT makes it vulnerable to cybersecurity threats. Especially, identity spoofing attacks, where an adversary passively listens to the existing radio communications and then mimic the identity of legitimate devices to conduct malicious activities. Existing solutions employ

Mobile-edge computing (MEC) is a new paradigm that provides cloud computing services at the edge of networks. To achieve better performance with limited computing resources, peer offloading between cooperative edge servers (e.g., MEC-enabled base stations) has been proposed as an effective technique to handle bursty and spatially imbalanced arrival of computation tasks. While various performance metrics

In Internet-of-Things (IoT)-driven smart-world systems, real-time crowdsourced databases from multiple distributed servers can be aggregated to extract dynamic statistics from a larger population, thus providing more reliable knowledge for our society. Particularly, multiple distributed servers in a decentralized network can realize real-time collaborative statistical estimation by disseminating statistics

Due to poor traffic conditions and the high costs of traveling by private cars, ride sharing has become a popular means to trip. In view of the security threats and centralization existing in the current ride-sharing service, we propose a secure ride-sharing scheme based on a consortium blockchain, which can guarantee the security, confidentiality, and privacy of data interaction via attribute-based

This article focuses on the secure routing problem in the decentralized Internet of Things (IoT). We consider a typical decentralized IoT scenario composed of peer legitimate devices, unauthorized devices (eavesdroppers), and selfish helper jamming devices (jammers), and propose a novel incentive jamming-based secure routing scheme. For a pair of source and destination, we first provide theoretical

One of the important Internet-of-Things applications is to use image and video to realize automatic people monitoring, surveillance, tracking, and reidentification (Re-ID). Despite some recent advances, pedestrian Re-ID remains a challenging task. Existing algorithms based on fully supervised learning for it usually requires numerous labeled image and video data, while often ignoring the problem of

With the emergence of 5G, wireless sensor networks, and related technologies, Internet of Things (IoT) has gained prominence as an emerging paradigm to meet the demands of flexible, agile, and ubiquitous accessibility of cyberspace from physical systems. However, the current centralized IoT architecture is heavily restricted by the problems of single points of failure, data privacy, security, and robustness

Mobile-edge computing (MEC) plays a significant role in enabling diverse service applications by implementing efficient data sharing. However, the unique characteristics of MEC also bring data privacy and security problem, which impedes the development of MEC. Blockchain is viewed as a promising technology to guarantee the security and traceability of data sharing. Nonetheless, how to integrate blockchain

The continuously increasing number of connected smart devices has led to the emergence of a crucial fault detection challenge to the Internet of Things (IoT). In this study, we aim to identify a method for the effective detection of faults in IoT devices. An IoT network model is first established, and a data edge verification mechanism based on blockchain is proposed; the blockchain is used to ensure

To cope with the unprecedented surge in demand for data computing for the applications, the promising concept of multiaccess edge computing (MEC) has been proposed to enable the network edges to provide closer data processing for mobile devices (MDs). Since enormous workloads need to be migrated, and MDs always remain resource-constrained, data offloading from devices to the MEC server will inevitably

Nonorthogonal multiple access (NOMA) significantly improves the connectivity opportunities and enhances the spectrum efficiency (SE) in the fifth generation and beyond (B5G) wireless communications. Meanwhile, emerging B5G services demand for higher SE in the NOMA-based wireless communications. However, traditional ground-to-ground (G2G) communications are hard to satisfy these demands, especially

In modern smart grids deployed with various advanced sensors, e.g., phasor measurement units (PMUs), bad (anomalous) measurements are always inevitable in practice. Considering the imperative need for filtering out potential bad data, this article develops a novel online bad PMU data detection (BPDD) approach for regional phasor data concentrators (PDCs) by sufficiently exploring spatial–temporal correlations

The combined cooling, heating and power (CCHP) system is a typical distributed, electricity-gas integrated energy scheme in a community. First, it generates electricity by use of gas, and then exploits the waste heat to supply community with heat and cooling. In this paper, we consider a smart city consisting of a number of communities (CCHPs) and an agent of power grid (APG), where CCHPs can sell

This research presents a new multichain routing strategy named the destination-oriented routing algorithm (DORA). The proposed design generates a new multichain routing scheme to transmit packets for energy-balanced WSNs. Based on the multichain routing, the optimal transmission distance between any two nodes is derived by the mathematical analysis model. With the optimal distance, the design criterion

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Object sensing and tracking using electric and magnetic fields allow intelligent interaction, automation, and adaptation in cyber–physical systems. Our approach, called iSense, uses a software-defined collaborative sensing technique for the detection of the type of object when placed on a large surface and tracking its mobility. iSense is cost effective, low power, and scalable, which allows its use

The recent advancement of the Internet of Things (IoT) enables the possibility of data collection from diverse environments using IoT devices. However, despite the rapid advancement of low-power communication technologies, the deployment of IoT networks still faces many challenges. In this article, we propose a hybrid, low-power, wide-area network (LPWAN) structure that can achieve wide-area communication

Smartphones, wearables, and Internet-of-Things (IoT) devices produce a wealth of data that cannot be accumulated in a centralized repository for learning supervised models due to privacy, bandwidth limitations, and the prohibitive cost of annotations. Federated learning provides a compelling framework for learning models from decentralized data, but conventionally, it assumes the availability of labeled

As wireless services and applications become more sophisticated and require faster and higher capacity networks, there is a need for an efficient management of the execution of increasingly complex tasks based on the requirements of each application. In this regard, fog computing enables the integration of virtualized servers into networks and brings cloud services closer to end devices. In contrast

In a time of arrival (TOA) or pseudorange-based positioning system, user location is obtained by observing multiple anchor nodes (ANs) at known positions. Utilizing more than one positioning systems, e.g., combining global positioning system (GPS) and BeiDou navigation satellite system (BDS), brings better positioning accuracy. However, ANs from two systems are usually synchronized to two different

Internet of Things (IoT) systems are of paramount importance to provide ubiquitous wireless connectivity for smart cities. However, such systems are facing security challenges due to the broadcast and openness nature of wireless channels. This article studies the performance of covert communication under a scenario consisted of a source–destination pair, a passive warden, and multiple relays. We first