In recent years, the concept of the Metaverse has attracted considerable attention. This article provides a comprehensive overview of the Metaverse. First, the development status of the Metaverse is presented. We summarize the policies of various countries, companies, and organizations relevant to the Metaverse, as well as statistics on the number of Metaverse-related publications. Characteristics of the Metaverse are identified: 1) multitechnology convergence; 2) sociality; and 3) hyper-spatio-temporality. For the multitechnology convergence of the Metaverse, we divide the technological framework of the Metaverse into five dimensions. For the sociality of the Metaverse, we focus on the Metaverse as a virtual social world. Regarding the characteristic of hyper-spatio-temporality, we introduce the Metaverse as an open, immersive, and interactive 3-D virtual world which can break through the constraints of time and space in the real world. The challenges of the Metaverse are also discussed.

The rapid growth of the Internet of Things (IoT) and the increasing number of connected devices have propelled the proliferation of offered applications, causing “applications exploding.” In the context of IoT, filtering and selecting the most relevant applications in a given situation is a challenging task. Thus, developing techniques that can alleviate applications exploding and meet users’ requirements is highly demanded for IoT development. This survey focuses on applications exploding in the IoT and reviews some of the existing techniques, such as intelligent sensing, content distribution network, microservices, and 5G, which help mitigate the effects of applications exploding. Furthermore, the survey discusses how to describe user requirements and offer application services to better match the two. In addition, this survey presents the smart home as an instance of typical IoT applications and explores how adaptive users’ requirements for food ordering can be better met when various food provider applications are available for choice. Finally, partially resolved and unresolved bottlenecks brought by applications exploding are put forward to be further researched by the technical and scientific community.

ZigBee is one of the communication protocols used in the Internet of Things (IoT) applications. In typical deployment scenarios involving low-cost and low-power IoT devices, many communication features are disabled, consequently affecting the security offered by ZigBee. The ZigBee specification assumes that deployment of frame counters is sufficient to mitigate replay attacks in secure ZigBee networks. However, we demonstrate that it is insufficient in this paper (i.e., the network is no longer secure after the coordinator restarts). As a countermeasure, we present a timestamp-based scheme to mitigate replay attacks. Our mitigation strategy does not consume power significantly, and fully powered devices will be responsible for providing power-constrained devices with the current timestamp. The proposed scheme is designed for all ZigBee topologies and different states of ZigBee End Devices (ZEDs). Findings from our evaluation show that the proposed scheme can successfully mitigate replay attacks, with no significant network performance degradation even assuming a worst-case scenario (i.e., many devices are sending data simultaneously).

The prevalence and large-scale uptake of the Internet of Things (IoT) have led to a growing trend of Identification Exploding, namely heterogeneous entities respectively identified to provide convenient intelligent services. To address challenges under Identification Exploding, unified modeling has become a promising approach to generalizing identification for heterogeneous entities in IoT. This paper surveys and discusses Identification Exploding's background to explore the possibility of unified modeling as one of the solutions. Meanwhile, challenges of realizing unified modeling are discussed. After that, comprehensive reviews on the latest modeling approaches and methods covering various IoT entities are carried out, including sensed entities and sensing devices. Special attention has been paid to modeling under resource-constrained IoT environments and relevant modeling-based industry solutions with critical analysis. It is proved that unified modeling is extremely significant under Identification Exploding Tendency in the IoT era.

With the recent advances of the Internet of Things (IoT), and the increasing accessibility to ubiquitous computing resources and mobile devices, the prevalence of rich media contents, and the ensuing social, economic, and cultural changes, computing technology and applications have evolved quickly over the past decade. They now go beyond personal computing, facilitating collaboration and social interactions in general, causing a quick proliferation of social relationships among IoT entities. The increasing number of these relationships and their heterogeneous social features have led to computing and communication bottlenecks that prevent the IoT network from taking advantage of these relationships to improve the offered services and customize the delivered content, known as social relationships explosion. On the other hand, the quick advances in artificial intelligence applications in social computing have led to the emerging of a promising research field known as artificial social intelligence (ASI) that has the potential to tackle the social relationships explosion problem. This article discusses the role of IoT in social relationships management, the problem of social relationships explosion in IoT, and reviews the proposed solutions using ASI, including social-oriented machine-learning and deep-learning techniques.

With the development of the cloud-based Internet of Things (IoT), people and things can request services, access data, or control actuators located thousands of miles away. The entity authentication of the remotely accessed devices is an essential part of the security systems. In this vein, physical unclonable functions (PUFs) are a hot research topic, especially for generating random, stable, and tamper-resistant fingerprints. This article proposes a lightweight, robust static random access memory (SRAM)-PUF-based entity authentication scheme to guarantee that the accessed end devices are trustable. The proposed scheme uses challenge-response pairs (CRPs) represented by reordered memory addresses as challenges and the corresponding SRAM cells' startup values as responses. The experimental results show that our scheme can efficiently authenticate resources-constrained IoT devices with a low computation overhead and small memory capacity. Furthermore, we analyze the SRAM-PUF by testing the PUF output under different environmental conditions, including temperature and magnetic field, in addition to exploring the effect of writing different values to the SRAM cells on the stability of their startup values.

Internet-of-Things (IoT)-enabled sensors and services have increased exponentially recently. Transmitting the massive generated data and control messages becomes an overhead on the communication system infrastructure. Many architectures and paradigms have been introduced to address the connection exploding, such as cloudlets, fog, and mist computing. Besides, software-related solutions, such as mobile Internet technologies and software-defined network also take part in mitigating the communication overhead. All of those new techniques have the same purposes summarized in achieving low latency, high throughput, and less storage and computing at the cloud level in addition to other objectives discussed through this survey. We list the proposed solutions, show their advantages and schemes, highlight some of the newest IoT-enabled applications, and show how they benefit from applying the new paradigms.