ABSTRACT
Metaverse is the latest technological hype in the modern world due to its potential for revolutionizing the digital visual perspective. With the COVID-19 pandemic, most industries have moved towards digitization, and the metaverse is identified as one of the most promising platforms for such a transition, as it provides a three-dimensional (3D) immersive experience for the users. Currently, most digital service providers and organizations are actively working on metaverse- based applications. In addition, there has been a rapid increase on research work involving metaverse realization. Launching a large scale metaverse in the real world is a challenging task. However, fifth-generation (5G) and beyond 5G (B5G) technologies are envisioned to improve the feasibility of pragmatic deployments. Although, there are several conceptual designs available, actual adaptations of the concepts are still limited. This survey focuses on providing a practical approach for metaverse realization using 5G and B5G technologies. Specifically, We discuss the importance of network slicing (NS) and multi-access edge computing (MEC) as emerging 5G technologies for enabling the realization of the metaverse. We first introduce the motivation behind metaverse for future envisaged technologies. Next, we present a holistic high-level framework for metaverse realization based on network slicing and edge computing. Moreover, we discuss the futuristic metaverse applications, their technical requirements, and methods to satisfy the requirements. Finally, we highlight the deployment challenges and possible approaches to overcome them for an actual metaverse realization. Author
ABSTRACT
Video streaming market has been growing rapidly for the past two decades. YouTube and Netflix, for example, are part of everyday life for many of us. Although network bandwidth has increased with the development of 5G and fiber, user demand and expectations have also increased with 4K videos, larger screens, and COVID-19. Recent explosive increase in video traffic made it difficult for the network and applications to satisfy the user requirements of video streaming. Multi-access edge computing (MEC) is a promising technology to resolve this problem. MEC is a network architecture concept that offers cloud-computing capabilities and an IT service environment at the edge of the network. In this paper, we review the research efforts in video streaming with MEC over the past few years. We have clustered and categorized the literature according to the optimization criteria, with focus on cache management. We aim this survey to be a cornerstone for designing effective novel caching scheme in MEC for video streaming. © 2022 IEEE.
ABSTRACT
Unmanned aerial vehicles (UAVs) extend the traditional ground-based Internet of Things (IoT) into the air. UAV mobile edge computing (MEC) architectures have been proposed by integrating UAVs into MEC networks during the current novel coronavirus disease (COVID-19) era. UAV mobile edge computing (MEC) shares personal data with external parties (such as edge servers) during intelligent medical analytics. However, this technique raises privacy concerns about patients' health data. More recently, the concept of federal learning (FL) has been set up to protect mobile user data privacy. Compared to traditional machine learning, federated learning requires a decentralized distribution system to enhance trust for UAVs. Blockchain technology provides a secure and reliable solution for FL settings between multiple untrusted parties with anonymous, immutable, and distributed features. Therefore, blockchain-enabled FL provides both theories and techniques to improve the performance of intelligent UAV edge computing networks from various perspectives. This survey begins by discussing the current state of research on blockchain and FL. Then, compare the leading technologies and limitations. Second, we will discuss how to integrate blockchain and FL into UAV edge computing networks and the associated challenges and solutions. Finally, we discuss the fundamental research challenges and future directions.
ABSTRACT
The COVID-19 pandemic has changed the world. Today, the use of Information and Communications Technology (ICT) in support of education, medicine, business and administration has become a reality practically everywhere. In particular, the eHealth (digital Health) sector is on the cusp of a revolution, fueled by the worldwide health emergency due to the spread of the new coronavirus. With a view to developing new sixth generation (6G)-oriented architectures, advanced eHealth services like telemonitoring would benefit from the support of technologies that guarantee secure data access, ultra-low latency and very-high reliability targets, which are hardly achievable by the fifth generation (5G). This is the reason why this work proposes an eHealth system architecture, in which low-latency enabling technologies like Device-to-Device (D2D) communications and Multi-access Edge Computing (MEC) are integrated and supported by security mechanisms for an optimal management of sensitive health data collected by Internet of Medical Things (IoMT) devices. A preliminary evaluation of the proposed framework is provided that shows promising results in terms of data security and latency reduction. IEEE