The advances in artificial intelligence (AI) have led to technological advancements in a plethora of domains. Healthcare, education, and smart city services are now enriched with AI capabilities. These technological advancements would not have been realized without the assistance of fast, secure, and fault-tolerant communication media. Traditional processing, communication, and storage technologies cannot maintain high levels of scalability and user experience for immersive services. The metaverse is an immersive three-dimensional (3D) virtual world that integrates fantasy and reality into a virtual environment using advanced virtual reality (VR) and augmented reality (AR) devices. Such an environment is still being developed and requires extensive research in order for it to be realized to its highest attainable levels. In this article, we discuss some of the key issues required in order to attain realization of metaverse services. We propose a framework that integrates digital twin (DT) with other advanced technologies, such as the sixth-generation (6G) communication network, blockchain, and AI, to maintain continuous end-to-end metaverse services. This article also outlines requirements for an integrated, DT-enabled metaverse framework and provides a look ahead into the evolving topic.

Network trustworthiness is considered a very crucial element in network security and is developed through positive experiences, guarantees, clarity, and responsibility. Trustworthiness becomes even more compelling with the ever-expanding set of Internet of Things (IoT) smart city services and applications. Most of today’s network trustworthy solutions are considered inadequate, notably for critical applications where IoT devices may be exposed and easily compromised. In this article, we propose an adaptive framework that integrates both federated learning and blockchain to achieve both network trustworthiness and security. The solution is capable of dealing with individuals’ trust as a probability and estimates the end devices’ trust values belonging to different networks subject to achieving security criteria. We evaluate and verify the proposed model through simulation to showcase the effectiveness of the framework in terms of network lifetime, energy consumption, and trust using multiple factors. Results show that the proposed model maintains high accuracy and detection rates with values of $\approx 0.93$ and $\approx 0.96$ , respectively.

The aerial capabilities and flexibility in movement of Unmanned Aerial Vehicles (UAVs) has enabled them to adaptively provide both traditional and more contemporary services. In this article, we introduce a solution that integrates the capabilities of both UAVs and Unmanned Ground Vehicles (UGVs) to provide both intelligent connectivity and services to both aerial and ground connected devices. A cooperative solution is adopted that considers nodes' power and movement constraints. The UAV and UGV cooperative process ensures continuous power availability to UAVs to support seamless and continuous service availability to end-devices. A Federated Learning (FL) approach is adopted at the edge to ensure accurate and up-to-date service provisioning in accordance with the surrounding environment and network constraints. Moreover, Blockchain technology is used to decentralize the provisioning and control aspects, and ensure authenticity and integrity. Extensive simulations are conducted to test the soundness and applicability of the proposed solution. Results show significant improvement in terms of connectivity, service availability, and UAV energy enhancements when compared to traditional mobile and vehicular communication techniques.