Jul 2026· International Journal of Science, Strategic Management and Technology· Vol 02, pp. 1-9· 0 citations
TL;DR
An intelligent Metaverse communication infrastructure that integrates 6G wireless networks, Multi-access Edge Computing, Software-Defined Networking (SDN), Network Function Virtualization (NFV), AI-driven resource management, and blockchain-enabled security to optimize communication performance in immersive environments is presented.
Abstract
The Metaverse is emerging as a next-generation digital ecosystem that integrates immersive virtual environments with real-time communication, artificial intelligence (AI), extended reality (XR), Internet of Things (IoT), blockchain, and cloud-edge computing technologies. However, supporting seamless interaction among millions of concurrent users requires a robust communication infrastructure capable of delivering ultra-low latency, high bandwidth, reliable connectivity, and secure data exchange. This paper presents an intelligent Metaverse communication infrastructure that integrates 6G wireless networks, Multi-access Edge Computing (MEC), Software-Defined Networking (SDN), Network Function Virtualization (NFV), AI-driven resource management, and blockchain-enabled security to optimize communication performance in immersive environments. The proposed architecture dynamically allocates network resources using machine learning-based traffic prediction, deploys edge intelligence for latency-sensitive applications, and employs blockchain for decentralized identity management and secure data transactions. Furthermore, digital twin-assisted network monitoring continuously analyzes communication conditions and enables proactive optimization to improve service reliability and Quality of Experience (QoE). Experimental evaluation demonstrates that the proposed framework significantly reduces communication latency, improves network throughput, enhances resource utilization, and strengthens security compared with conventional cloud-centric communication architectures. The proposed infrastructure provides a scalable, intelligent, and secure communication framework for future Metaverse applications, including virtual collaboration, digital healthcare, industrial automation, online education, and immersive entertainment.
The intersection of sixth-generation (6G) communication networks, edge computing, and federated learning offers a novel occasion regarding empowering trustful and scalable collaboration throughout distributed Internet of Things (IoT) ecosystems. Conventional centralized machine learning technology is plagued by severe constraints in IoT scenes, such as privacy issues, network congestion, and network bottlenecks. The paper has presented a new 6G-integrated federated learning system which builds on the native intelligence of 6G networks to support secure, efficient, and scalable cooperative learning among heterogeneous edge-IoT devices. The suggested architecture combines terahertz frequencies to synchronize model communication in real-time at ultra-low latency, reconfigurable intelligent surfaces to improve the quality of communication, and network slicing to provide differentiated quality-of-service assurances. Another new hierarchical federated learning system integrates intra-edge aggregation and inter-edge cooperation that can reduce communication overhead by 85-percent and achieve the same accuracy in models. This framework integrates blockchain-based trust management involving zero-knowledge proofs of verifiable model update, to provide integrity and accountability without impacting on privacy. Experimental analysis of massive scale edge-IoT applications has revealed that the suggested scheme attains 97.2% model precision and lowers communication expenses by 87 percent and convergence rate by 3.4 times that of traditional federated learning techniques. The framework has high-uniform performance in adversarial environments where 99.6 percent of malicious model updates are identified with a small false positive. The results define the 6G-integrated federated learning as a framework of reliable and scalable edge-IoT cooperation.
T.Muthumanickam, D. Jayalakshmi, Sathiyamoorthy M et al.· 2026 6th International Confe...· 0 citations
This paper presented an Intelligent Edge Computing Framework for Secure, Low-Latency, and Energy-Efficient Smart Devices that integrates edge intelligence, adaptive task scheduling, resource-aware computation, secure communication, and cloud-assisted services to address the limitations of conventional cloud-centric architectures. By processing data closer to smart devices, the proposed framework significantly reduces latency, minimizes network bandwidth consumption, improves resource utilization, and enables faster real-time decision-making while ensuring data privacy and security. The experimental results demonstrate superior performance in terms of classification accuracy, ROC-AUC, Average Precision, execution time, and computational efficiency compared with existing cloud-based and edge computing approaches. The proposed framework provides a scalable, reliable, and energy-efficient solution for diverse Internet of Things (IoT) applications, including smart healthcare, industrial automation, intelligent transportation, and smart homes. Future work will focus on integrating federated learning, blockchain-enabled security, and next-generation 6G edge intelligence to further enhance scalability, privacy preservation, and autonomous decision-making in large-scale smart device ecosystems.
Kolipaka Vinay, Valusa Venkat Sai Kumar, D. A. Kumar· International Journal of Sci...· 0 citations
Distributed Ledger Technologies (DLTs) have turned out to be an underlying enabler of trust, security, and automation in the next-generation wireless networks (6G). Contrasting centralized control models, the DLTs offer decentralized coordination, record keeping which is immutable, and programmable logic, which is consistent with the ultra-dense and intelligent heterogeneous ecosystems of 6G. The paper has discussed the performance implications of incorporation of the SDLTs with 6G networks in blockchain, directed acyclic graph based ledger and hybrid DLT architectures. There was an integrated DLT-6G framework where cross-layer communication between radio access, core, edge computing, and distributed ledgers was highlighted. To model the latency of transactions, their throughput, energy usage, and consensus overhead were modeled based on the 6G communication characteristics including ultra-low latency, massive connectivity, and edge intelligence. A large-scale set of simulations was done to test the DLT-based network slicing, secure resource orchestration, and AI-assisted ledger management and compared the results to that of traditional non-DLT methods. The results have shown that lightweight and DAG-based DLTs were much more cost-effective in terms of confirmation delay and energy usage, whereas in dense 6G operation, hybrid designs were more scalable and dependable. Moreover, ledger management with the help of AI improved flexibility in changing the conditions of traffic and mobility.
Snehankita Majalekar, Awantika Bijwe, Vimal Bibhu et al.· Journal of Intelligent Decis...· 0 citations
The rapid deployment of sixth-generation (6G) Internet of Things (IoT) networks demands lightweight authentication mechanisms that provide low latency, high scalability, and robust security for resource-constrained devices operating in dynamic wireless environments. Conventional authentication approaches based on Transport Layer Security (TLS) and Datagram Transport Layer Security (DTLS), blockchain-assisted architectures, and Generic Bootstrapping Architecture (GBA)-based schemes introduce significant computational complexity, communication overhead, synchronization delays, and infrastructure dependencies, limiting their suitability for large-scale edge-assisted IoT environments. This paper proposes Lightweight Timed Efficient Stream Loss-Tolerant Authentication over the Constrained Application Protocol (L-TESLA-CoAP), a lightweight and infrastructure-independent authentication framework that integrates adaptive TESLA delayed-key authentication, CoAP communication, edge-assisted synchronization, replay-aware synchronization, SHA3-HMAC-based symmetric authentication, and rotating pseudonym identities to provide continuous packet-level authentication. The proposed framework was implemented and evaluated using a Python-based simulation environment under constrained 6G IoT communication scenarios with network sizes ranging from 50 to 1000 IoT devices. The comparative evaluation against CoAP, DTLS, TLS, Blockchain-CoAP, and GBA-Hybrid TESLA shows that the proposed framework achieves low authentication latency (approximately 0.8–1.3 s) and low energy consumption (approximately 60–75 mJ) while maintaining packet-loss recovery capability, reduced communication overhead, reduced computation time, low memory consumption, and authentication throughput. Furthermore, the proposed framework provides resilience against replay, packet injection, impersonation, synchronization manipulation, and denial-of-service attacks through adaptive synchronization and delayed key disclosure. These results indicate that L-TESLA-CoAP provides an efficient, scalable, and lightweight authentication solution suitable for next-generation edge-assisted 6G IoT applications.
The evolution of wireless communication has significantly transformed the way information is generated, transmitted, and processed across various sectors. As the demand for high-speed, low-latency, and highly reliable communication continues to increase, Fifth Generation (5G) wireless technology has emerged as a key enabler of the future information era. Unlike previous generations of mobile communication, 5G offers enhanced mobile broadband, ultra-reliable low-latency communication, and massive machine-type communication, enabling seamless connectivity among billions of interconnected devices. These capabilities support the rapid growth of emerging technologies, including the Internet of Things (IoT) and Artificial Intelligence (AI) cloud computing, edge computing, autonomous transportation, Industry 4.0, smart healthcare, and smart city infrastructures. Despite its numerous Despite these benefits, several challenges persist, including the high costs associated with implementation, cybersecurity threats, spectrum scarcity, interoperability issues, energy consumption, and privacy concerns. This paper presents a comprehensive review of 5G technology and its applications in the future information era. It discusses the architecture of 5G networks, analyzes major application domains, examines current technical and economic challenges, identifies existing research gaps, and explores future research directions. The study concludes that although 5G provides the technological foundation for next-generation digital transformation, continued research is required to improve network security, intelligent resource allocation, sustainable deployment, and integration with future sixth-generation (6G) communication systems.
E. M. Tanuja, Basavaraj S. Pol· International Journal of Res...· 0 citations
The analysis indicates that effective edge-cloud AI systems require adaptive workload placement, privacy-preserving distributed learning, security-aware inference, explainability, fault tolerance, and continuous resource optimization rather than simple physical distribution of computation.
Dr. Amir Hosseini, dr.nematollah karimi· International Journal of Adv...· 0 citations
