The rapid development of blockchain technology and their numerous emerging applications has received huge attention in recent years. distributed consensus mechanism is the backbone a network. It plays key role ensuring network's security, integrity, performance. Most current networks have been deploying proof-of-work mechanisms, which reached through intensive mining processes. However, this several limitations, e.g., energy inefficiency, delay, vulnerable to security threats. To overcome...

Future 5th generation networks are expected to enable three key services-enhanced mobile broadband, massive machine type communications and ultra-reliable low latency (URLLC). As per the 3rd partnership project URLLC requirements, it is that reliability of one transmission a 32 byte packet will be at least 99.999% most 1 ms. This unprecedented level yield various new applications, such as smart grids, industrial automation intelligent transport systems. In this survey we present potential...

In this paper, we propose novel approaches using state-of-the-art machine learning techniques, aiming at predicting energy demand for electric vehicle (EV) networks. These methods can learn and find the correlation of complex hidden features to improve prediction accuracy. First, an (EDL)-based solution in which a charging station provider (CSP) gathers information from all stations (CSs) then performs EDL algorithm predict considered area. However, approach requires frequent data sharing...

Social distancing plays a pivotal role in preventing the spread of viral diseases illnesses such as COVID-19. By minimizing close physical contact among people, we can reduce chances catching virus and spreading it across community. This paper aims to provide comprehensive survey on how emerging technologies, e.g., wireless networking, artificial intelligence (AI) enable, encourage, even enforce social practice. To that end, first background including basic concepts, measurements, models,...

Metaverse has recently attracted paramount attention due to its potential for future Internet. However, fully realize such potential, applications have overcome various challenges as massive resource demands, interoperability among applications, and security privacy concerns. In this paper, we propose MetaChain, a novel blockchain-based framework address emerging the development of applications. particular, by utilizing smart contract mechanism, MetaChain can effectively manage automate...

The growing interest in the Metaverse has generated momentum for members of academia and industry to innovate toward realizing world. is a unique, continuous, shared virtual world where humans embody digital form within an online platform. Through avatar, users should have perceptual presence environment can interact control around them. Thus, human-centric design crucial element Metaverse. human are not only central entity but also source multi-sensory data that be used enrich ecosystem. In...

Effective network slicing requires an infrastructure/network provider to deal with the uncertain demands and real-time dynamics of resource requests. Another challenge is combinatorial optimization numerous resources, e.g., radio, computing, storage. This paper develops optimal fast framework that maximizes long-term return while taking into account uncertainty from tenants. Specifically, we first propose a novel system model enables effectively slice various types resources different...

With the rapid growth of mobile applications and cloud computing, computing has attracted great interest from both academia industry. However, are facing security issues such as data integrity, users' confidentiality, service availability. A preventive approach to problems is detect isolate cyber threats before they can cause serious impacts system. In this paper, we propose a novel framework that leverages deep learning cyberattacks in environment. Through experimental results, show our...

The digital revolution has substantially changed our lives in which Internet-of-Things (IoT) plays a prominent role. rapid development of IoT to most corners life, however, leads various emerging cybersecurity threats. Therefore, detecting and preventing potential attacks networks have recently attracted paramount interest from both academia industry. Among attack detection approaches, machine learning-based methods, especially deep learning, demonstrated great thanks their early capability....

This two-part paper aims to provide a comprehensive survey on how emerging technologies, e.g., wireless and networking, artificial intelligence (AI) can enable, encourage, even enforce social distancing practice. In Part I, an extensive background of is provided, enabling technologies are thoroughly surveyed. this II, such as machine learning, computer vision, thermal, ultrasound, etc., introduced. These open many new solutions directions deal with problems in distancing, symptom prediction,...

With conventional anti-jamming solutions like frequency hopping or spread spectrum, legitimate transceivers often tend to "escape" "hide" themselves from jammers. These reactive approaches are constrained by the lack of timely knowledge jamming attacks (especially smart jammers). Bringing together latest advances in neural network architectures and ambient backscattering communications, this work allows wireless nodes effectively "face" jammer (instead escaping) first learning its strategy,...

We propose two novel proactive cooperative caching approaches using deep learning (DL) to predict users' content demand in a mobile edge network. In the first approach, server (CS) takes responsibilities collect information from all nodes (MENs) network and then performs proposed DL algorithm for whole However, such centralized approach may disclose private because MENs have share their local data with CS. Thus, second we distributed (DDL)-based framework. The DDL allows collaborate exchange...

With outstanding features, machine learning (ML) has become the backbone of numerous applications in wireless networks. However, conventional ML approaches face many challenges practical implementation, such as lack labeled data, constantly changing environments, long training process, and limited capacity devices. These challenges, if not addressed, can impede effectiveness applicability To address these problems, transfer (TL) recently emerged to be a promising solution. The core idea TL...

Intrusion detection (ID) on the cloud environment has received paramount interest over last few years. Among latest approaches, machine learning-based ID methods allow us to discover unknown attacks. However, due lack of malicious samples and rapid evolution diverse attacks, constructing a system (IDS) that is robust wide range attacks remains challenging. In this article, we propose novel solution enable IDSs using deep neural networks. Specifically, develop two generative models synthesize...

Creating and maintaining the Metaverse requires enormous resources that have never been seen before, especially computing for intensive data processing to support Extended Reality, storage resources, massive networking ultra high-speed low-latency connections. Therefore, this work aims propose a novel framework, namely MetaSlicing, can provide highly effective comprehensive solution in managing allocating different types of applications. In particular, by observing applications may common...

The recent evolution of generative artificial intelligence (GAI) leads to the emergence groundbreaking applications such as ChatGPT, which not only enhances efficiency digital content production, text, audio, video, or even network traffic data, but also enriches its diversity. Beyond creation, GAI's capability in analyzing complex data distributions offers great potential for wireless communications, particularly amidst a rapid expansion new physical layer communication technologies. For...

Freezing of gait (FoG) is common in Parkinsonian and strongly relates to falls.Current clinical FoG assessments are patients' self-report diaries experts' manual video analysis.Both subjective yield moderate reliability.Existing detection algorithms have been predominantly designed subject-dependent settings.In this work, we aim develop an automated detector for subject-independent.After extracting highly relevant features, apply anomaly techniques detect events.Specifically, feature...

Although the development of IoT Industry 4.0 has brought breakthrough achievements in many sectors, e.g., manufacturing, healthcare, and agriculture, it also raises security issues to human beings due a huge emerging cybersecurity threats recently. In this paper, we propose novel collaborative learning-based intrusion detection system which can be efficiently implemented 4.0. under consideration, develop smart "filters" deployed at gateways promptly detect prevent cyberattacks. particular,...

This paper investigates the coexistence of non-orthogonal multiple access (NOMA) and full-duplex (FD) to improve both spectral efficiency (SE) user fairness. In such a scenario, NOMA based on successive interference cancellation technique is simultaneously applied uplink (UL) downlink (DL) transmissions in an FD system. We consider problem jointly optimizing association (UA) power control maximize overall SE, subject user-specific quality-of-service total transmit constraints. To be...

Internet of Things (IoT) has emerged as a cutting-edge technology that is changing human life. The rapid and widespread applications IoT, however, make cyberspace more vulnerable, especially to IoT-based attacks in which IoT devices are used launch attack on cyber-physical systems. Given massive number (in order billions), detecting preventing these critical. However, this task very challenging due the limited energy computing capabilities continuous fast evolution attackers. Among attacks,...

In this paper, we propose a novel economic-efficiency framework for an electric vehicle (EV) network to maximize the profits (i.e., amount of money that can be earned) charging stations (CSs). To end, first introduce energy demand prediction method CSs leveraging federated learning approaches, in which each CS train its own transactions locally and exchange learned model with other improve quality while protecting CS's information privacy. Based on predicted demands, reserve from smart grid...

We investigate the performance of multi-user multiple-antenna downlink systems in which a base station (BS) serves multiple users via shared wireless medium. In order to fully exploit spatial diversity while minimizing passive energy consumed by radio frequency (RF) components, BS is equipped with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> RF chains and...