Extended Reality (XR) is one of the major innovations to be introduced in 5G/5G-Advanced communication systems. A combination of augmented reality, virtual reality, and mixed reality, supplemented by cloud gaming, revisits the way that humans interact with computers, networks, and each other. However, efficient support of XR services imposes new challenges for existing and future wireless networks

With the potential of reshaping the future of mobility, connected and autonomous vehicles (CAVs) offer a potential opportunity to transform the world with significant social, industrial, and economic benefits. One major challenge of CAVs is the driving safety while meeting the occlusions. To resolve this problem, the researches on various types of sensor technologies and inference models have been

The articles in this special issue focus on the latest research and identify future opportunities for multi-user extended reality and the Metaverse. Immersive technologies, such as virtual, augmented, and mixed reality (VR, AR, and MR), which are often referred to as a universal term - extended reality (XR), have enabled numerous appealing applications in education, training, entertainment, healthcare

Distributed cloud systems bring new experiences to various cloud platform-based intelligent applications. Compared with traditional centralized cloud services, they give a greater network performance and lower service latency. However, the complexity of network structure and the diversity of IoT devices pose higher requirements for device authentication in distributed cloud systems. For example, shorter

Deep reinforcement learning (DRL) has been widely used to find optimal routing schemes to meet various demands of users. However, the optimization goal of DRL is typically static, whereas the network environment is dynamic. Changes in traffic environment or reconfiguration of network equipment often lead to periodic changes in network performance (e.g., throughput degradation and latency peaks). The

Federated learning in mobile edge computing allows a larger number of devices to jointly train an accurate machine learning model without collecting local data from edge nodes. However, there are two major challenges to using federated learning for mobile edge computing. The first is that mobile edge computing networks only tolerate a limited communication overhead, that is, communication overhead

Energy-availability prediction algorithms based on neural networks and random forests have enabled energy-neutral operation on resource-constrained sensors powered by energy harvesting. Coupled with careful energy management, the energy harvesting-aware sensors can sustain perpetual uptime, provided that the energy consumption is smaller than the harvested energy. Despite recent algorithmic advancements

Motivated by rising voices of light weight high security for the Industrial Internet of Things (IIoT), in this article, we propose a cross-layer authentication scheme by taking advantage of both the radio frequency fingerprinting (RFF) and the blockchain trust. Due to the mobility of terminal devices in the IIoT network, the wireless terminal devices often move from one region to another region, which

Autonomous vehicles could fundamentally alter the way we travel as they offer an unprecedented level of comfort and safety on the roads, including the ability to navigate and park in an appropriate spot. To enable this, robust turn-by-turn navigation tools and curbside parking planning tools are essential to ensure safe and efficient navigation, as they require the vehicle to understand and adhere

The metaverse refers to the merger of technologies for providing a digital twin of the real world and the underlying connectivity and interactions for the many kinds of agents within. As this set of technology paradigms-involving artificial intelligence, mixed reality, the Internet of Things, and others-gains in scale, maturity, and utility there are rapidly emerging design challenges and new research

Metaverse is the concept of a fully immersive and universal virtual space for multiuser interaction, collaboration, and socializing; forming the next evolution of the Internet. Metaverse depends on the convergence of multiple broad technologies that enable eXtended Reality (XR), which is an umbrella term for technologies that lie on the reality-virtuality continuum, namely Virtual Reality (VR), Augmented

Mobile augmented reality (MAR) blends a real scenario with overlaid virtual content, which has been envisioned as one of the ubiquitous interfaces to the Metaverse. Due to the limited computing power and battery life of MAR devices, it is common to offload the computation tasks to edge or cloud servers in close proximity. However, existing offloading solutions developed for MAR tasks suffer from high

Novel and cutting-edge use cases have arisen since the first deployments of the fifth generation (5G) of mobile communications. We can already find multiple 5G simulators and emulators in the state-of-the-art which allow engineers and researchers to thoroughly study and test the network. However, the 5G ecosystem is not only limited to the network itself, a fast development of 5G-specific use cases

A distributed cloud, connecting multiple smaller and geographically distributed data centers, can provide a significant alternative to the traditional model of massive and centralized data centers. Erasure coding is a key solution for improving the efficiency of storage resources in a distributed cloud. However, current end-side based erasure coding systems require significant computing resources because

The articles in this special section focus on the interplay between machine learning and networking systems.

Network traffic data prediction plays a significant role in various network applications and is a fundamental task in network traffic engineering. However, with the development of the Internet of Things and mobile computing, network traffic data presents the characteristics of high volume, variety, and velocity, which brings unprecedented challenges to network traffic data prediction. In this article

Network configuration translation is proposed to solve the problem of configuration migration and backup in the process of network configuration management, and how to automate configuration translation is an important issue in the development of autonomous driving network. It is of great scientific significance and application value to intellectualize network configuration management via artificial

Over the past few decades, a tremendous amount of research attention has been received to derive the network performance estimation problem. In its context, network performance estimators can provide an early-stage prediction before emulation and real-world deployment, which is essential for network design and optimization. The design philosophy of network performance estimators is to design accurate

Reinforcement learning (RL) is a critical enabler for optimizing performance, automating the deployment, and increasing the intelligence level of 6G networks. In this article, we first identify some advanced RL frameworks for diversified 6G service scenarios. We then envision RL-based intelligent network management for 6G from three different perspectives: cross-layer end-to-end network control for

The recent advances in 5G and mobile edge computing facilitate the rapid development of the Internet of Things (IoT), enabling collective intelligence with data support from a massive number of IoT devices. Meanwhile, federated learning (FL) has emerged as a promising solution for collaborative training while preserving user privacy, which, however, is prone to poor learning performance in large-scale

With the advent of emerging IoT applications, such as autonomous driving, digital-twin, metaverse, etc., featuring massive data sensing, analyzing, inference, and critical latency in beyond 5G (B5G) networks, edge artificial intelligence (AI) has been proposed to provide high-performance computation of a conventional cloud down to the network edge. Recently, the convergence of wireless sensing, computation

Rapid growth in distributed streaming data at the network edge in many applications has prompted the emergence of online federated learning (OFL), a promising distributed machine learning paradigm where multiple agents cooperate to perform online learning via a central server. Despite its distinctive capability in handling various real-world applications, OFL has yet to be widely adopted in the industry

As a novel distributed machine learning scheme, federated learning (FL) efficiently realizes the collaborative training of models by global participants while also protecting their data privacy. Due to the independence of participants' local data and the inability of the FL server to access the local data, many IIoT applications with strong data sensitivity are increasingly incorporating FL technology

Livecast in metaverse, such as Metaverse Concert, is gaining momentum, however, its extremely compute-intensive and delay-sensitive features challenge the ability of current computing paradigm. Besides, decentralization, which is one of the core ideas of the metaverse, drives the move away from cloud computing and edge computing. Hence, it urges a trustworthy, robust, and efficient intelligent computing

In this era of rapid technological advancement, characterized by remarkable progress in sensing, communication, networking, and computing, a groundbreaking concept emerges: Connected and Autonomous Vehicles (CAV), representing a beacon of innovation. Imagine a future where vehicles seamlessly monitor their internal health, accessing an array of onboard units to elevate transportation safety to unprecedented

Real-time driver emotion recognition and timely risk warning can effectively reduce the incidence of traffic accidents. However, existing emotion recognition methods obtain emotion features from human physiological signals and are unsuitable for complex scenarios in the Internet of Vehicles (loV). Moreover, the existing methods in the IoV cannot fully use the resources of edge devices for mining the

This study analyzes the feasibility of supporting critical V2X services using 5G network-based Vehicle-to-Network-to-Vehicle (V2N2V) communications. The study evaluates the end-to-end latency of 5G V2N2V communications under different network deployments in single and multi-operator scenarios. The study shows that critical V2X services can be supported using 5G V2N2V communications over MEC-based network

Digital twins are virtual replicas of the real world that capture precise interactions between actual devices and the environment in which they operate. Enabled by advancements in computing and ubiquitous software, digital twins may receive data from the real world as well as generate virtual datasets for making decisions that ultimately influence the complex real-world actions. As a use case, we propose

According to society of automotive engineers (SAE)'s standard J3016, there are six levels of driving automation, ranging from no driving automation (level 0) to full driving automation (level 5). In order to make autonomous vehicles (AVs) fully automated when driving, they must be capable of comprehending the driving environment, which requires the assistance of 5G networks and multi-access edge computing

Despite the recent successes of deep reinforcement learning, there still remain challenges for its real-world applications, such as autonomous vehicles. There are two main issues: sample inefficiency and poor generalization. In this article, we propose a novel method, called MHRL-I, short for meta hierarchical reinforcement learning with imitation learning, to improve the sample efficiency and learn

Autonomous Connected Internet of Vehicles (Auto-CloV) technology had demonstrated remarkable results in the near past. Due to its unprecedented contributions, both the public and government authorities have shown interest in this emerging technology by keeping in view its low cost, least accident rate, and on-demand controllability. Although this technology has numerous advantages over traditional

Unmanned aerial vehicles (UAVs) are promising for providing communication services due to their advantages in cost and mobility, especially in the context of the emerging Metaverse and Internet of Things (IoT). This article considers a UAV-assisted Metaverse network, in which UAVs extend the coverage of the base station (BS) to collect the Metaverse data generated at roadside units (RSUs). Specifically

The conventional network infrastructure is struggling to keep up with the rapidly growing demands of modern society. The explosion of data, the increasing number of connected devices, and the growing reliance on real-time applications are all putting pressure on the current network, which almost reaches Shannon's limit. In this article, we propose Meta-Networking, an advanced networking architecture

Having an accurate and comprehensive understanding of surrounding environment is the first step toward autonomous driving. For an autonomous car to plan its actions, for example, to make instant decisions about whether to proceed at an intersection or slow down to wait until a pedestrian crosses the road, it first needs to recognize its surroundings, including but not limited to vehicles and pedestrians

Advanced autonomous driving requires a holistic scene understanding and spatial-temporal evolving maps. Contrast to the common approach of problem decomposition, we advocate the philosophy of unification for scene perception and mapping toward modern autonomous vehicle systems. In this article, we first propose a unified framework to integrate multiple perception tasks into a single end-to-end deep

Global megatrends, such as urbanization, population growth, and emerging network solutions are accelerating the development of the Connected and Autonomous Vehicles (CAVs) industry. There are many truths, some misconceptions, and even some excitement about CAVs in the public's opinion. The main objective of the current article is to provide a comprehensive review, eliminate misconceptions, and outline

Vehicle-to-X (V2X) with specific user-defined performance metrics emerges as one vital application scenario in sixth generation (6G) networks. According to released reports and whitepapers, 6G networks are designed to have softwarization attributes. Through softwarization, tailored V2X services, constituted by softwarized (resource and function) blocks, can be deployed on top of underlying network

Precision agriculture and aging farming populations have given rise of autonomous farm vehicles to help reduce labor cost, save agriculture resources, and improve farming productivity. Unlike self driving on city roads or in dedicated facilities, autonomous vehicles on farmlands face a very different set of challenges. For example, large farms lack network coverage, the dynamics of the farm landscape

The complexity of orchestrating Beyond 5G services, such as vehicular, demands novel approaches to remove limitations of existing techniques, as these might cause a large delay in orchestration operations, and thus, negatively impact the service performance. For instance, the human-in-the-loop approach is slow and prone to errors, and closed loop control using rule-based algorithms is difficult to

With the increased number of vehicles, infrastructure, and demand for various road services, the traditional Internet of Vehicles (IoV) architecture fails to provide quality services to users. New frameworks combining the vehicular network with cloud computing to extend storage capacity and processing power are highly sought. The vehicles communicate with the roadside units (RSUs) and upload the road

The destruction of terrestrial infrastructure following natural disasters poses a significant challenge for emergency rescue and recovery operations. In this article, we propose an innovative solution called the aerial-ground cooperative vehicular network (AGCVN) to address this issue. The AGCVN aims to provide a reliable, flexible, and resilient integrated localization and communication (ILAC) service

The Scanning the Literature column provides concise summaries of selected papers that have recently been published in the field of networking. Each summary describes the paper's main idea, methodology, and technical contributions. The purpose of the column is to bring the state of the art of networking research to readers of IEEE Network. Authors are also welcome to recommend their recently published

As requirements for 6G systems start being shaped, we propose the provoking vision that the future generations of mobile networks shall reach beyond their traditional role of enablers for communication services. In fact, mobile networks have an impressive untapped potential for dual use as a pervasive remote sensing platform, which, if duly exploited, can support compelling original applications across

The IoT world is evolving with the latest technology trends, like edge computing, augmented & virtual reality, machine learning, robotics, and 5G. With the digital transformation happening in Industry 4.0, many industries are moving toward private 5G networks. There are massive number (hundreds to thousands) of IoT devices in a single factory depending on the scale of the industry and these factories

The emergence of Web 3.0 marks a historic turning point. It ushers in a new era in the history of the web, one defined by a radical transfer of access, ownership, and governance from today's crop of Internet giants to the Internet's every user. The idea behind Web 3.0 is to create an internet that accurately interprets your input, understands what you convey, and allows complete control over what type

With the standardization of 5G systems, research focus is slowly shifting towards potential designs, use cases, and performance targets for 6G systems. To meet the escalating data demands of mobile devices and to deal with the deluge of data, as well as the high-rate connectivity required by bandwidth-thirsty applications (e.g., space-air-ground-integrated-networks (SAGINs), augmented reality (AR)

The massive deployment of the fifth generation (5G) wireless networks are significantly accelerating the ongoing process of industrial and societal transformation. Disregard many impressive achievements, current scenario-specific, and communication-centric 5G technologies still face many challenges in empowering future applications with diverse requirements under stringent resource constraints. In

With the blooming of Internet-of-Things (IoT), we are witnessing an explosion in the number of IoT terminals, triggering an unprecedented demand for ubiquitous wireless access globally. In this context, the emerging low-Earth-orbit satellites (LEO-SATs) have been regarded as a promising enabler to complement terrestrial wireless networks in providing ubiquitous connectivity and bridging the ever-growing

Multiple access technology plays an important role in communication systems, which can enable different users to access the system efficiently and reliably. However, the conventional multiple access technologies are not suitable for future sixth generation (6G) systems as ultra-high reliability, extremely low latency, and massive connectivity should be supported. Unsourced random access (URA), where

The integrated satellite-terrestrial communication network (ISTCN) has become an important research direction for future sixth-generation mobile networks to meet the communication demands of seamless global coverage and anytime access. In ISTCN, terrestrial terminals and satellite terminals can share the same spectrum resources, so the spectrum resources available to the satellite system are unevenly

The sixth generation (6G) mobile communication systems could serve new multimodal services, such as virtual reality (VR), augmented reality (AR), holographic projection. These new services are accompanied by new demands for intelligence, personalization and collaboration. Semantic communications are increasingly attracting attention due to its potential to support the aforementioned multimodal services

Index modulation multiple access (IMMA) is a promising sixth-generation (6G) technique to prominently improve the spectral efficiency, energy efficiency, system performance, and support massive connectivity, which is considered as a new extension of conventional non-orthogonal multiple access (NOMA). In this article, we first introduce the basic principle of IMMA, and then investigate the potential

Smart community networks bring great comfort and convenience for people, but also increase security risks of exposing system vulnerabilities and private data to network intruders. This problem has become more prominent as the ever-increasing zero-day attacks which may escape the existing intrusion detection system (IDS) through unknown vulnerabilities. In this article, to keep up with the continuous

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Presents concise summaries of selected papers that are recently published in the field of networking. Each summary describes the paper's main idea, methodology, and technical contributions. The purpose of the column is to bring the state of the art of networking research to readers of IEEE Network. Authors are also welcome to recommend their recently published work to the column, and papers with novel

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