Toward an Evolvable 6G Telco Cloud Infrastructure: Enabling Service Provision and Experimental Validation

Emulating the SDN-Enabled Computing Continuum through Lightweight Virtualization

This work introduces an emulation framework that allows developers and operators to decide how to deploy networks, computing devices, and applications in a Computing Continuum environment, ensuring compliance with established Quality of Service standards.

Cloud-Native Architectures for Scalable Enterprise Applications

Cloud-native architecture has been the new paradigm in enterprise application development that facilitates organization to reach unprecedented levels of scalability, agility, reliability, and operational efficiency. The dynamic business requirements, short delivery cycles of software solutions and the necessity of globally distributed services are mounting an increasing challenge on traditional monolithic systems. The concepts of microservices architecture, containerization, DevOps culture, and continuous delivery pipelines are the main principles in cloud-native systems that circumvent the limitations. This paper will be a detailed study of cloud-native architecture and its strategic role in a digital transformation process of businesses. Scalability models, distributed resource management, service orchestration, elasticity patterns and resilience techniques applied by cloud-native platforms are further detailed in the abstract. We address the transformation of enterprise application infrastructure out of on-premise legacy resource setting into service-based cloud environments properly configured to scale horizontally. The paper also investigates that the container orchestration systems such as Kubernetes make deployment, scaling, and failover operations to be declaratively automated. The purpose of service mesh, API-oriented architecture, event-based systems, policy-oriented autoscaling, and infrastructure-as-code (IaC) are examined to show how the architectural resilience and operational administration are accomplished. An approach to assess the maturity of cloud-native systems is presented based on the performance benchmarking, lifecycle automation, security compliance, and cost optimization indicators as part of a methodological framework. Also, the paper presents experimental evaluations of the response time, throughput, service resiliency, and infrastructure utilization in both traditional and cloud-native deployments. Findings indicate the application availability, frequency of deployment and scalability efficiency are very high. Lastly, such challenges as state management, data consistency, complexities in migrating, observability, and operational complexity are also addressed. The innovations that are emphasized by the best practices and future-oriented thinking include serverlesscomputing, auto-scaling that is run with AI, workloads based on WebAssembly, and automated cloud operations. All in all, the paper points to the idea that cloud-native architectures are not something the enterprises can afford to ignore on their quest towards maintaining competitive viability in the rapidly changing digital economy.

Edge–Cloud Orchestration for IoT Services: Technologies, Architectures, and Research Directions

The advent of 6G networks and the rapid growth of Internet of Things (IoT) are revolutionizing the telecommunication sector, integrating edge-cloud systems with vast amounts of data from IoT and AI techniques. These advancements make these systems essential in managing and delivering a multitude of services, offered by smart cities and industrial domains, being just a few among the many possible application scenarios. Specifically, this shift introduces complexities in orchestrating services and managing available resources while addressing challenges such as reducing latency, growing bandwidth, ensuring trust, and integrating different technologies. In this sense, this review explores the recent approaches of the state of the art focused on service orchestration in IoT edge-cloud environments, concentrating on architectures and methodologies that enable resource allocation and service management. Furthermore, it examines platforms for orchestration development, highlighting their characteristics and contributions. Finally, emerging concerns such as network topology and trust, which previous surveys have often overlooked, are discussed together with the most relevant research directions.

Programmable B5G Infrastructure for Vertical-Aware Slice Orchestration: Teleoperation in Dynamic 5G Environments

An Intelligent 6G-Enabled Communication Infrastructure for Secure and Low-Latency Metaverse Applications

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.

Advancements in Cloud Infrastructure Automation: A Survey of Current Technologies and Future Trends

Cloud infrastructure automation has emerged as a pivotal component in modern cloud computing, enabling efficient resource management, rapid deployment, and enhanced scalability. This paper provides a comprehensive survey of current technologies in cloud infrastructure automation, including Infrastructure as Code (IaC), configuration management, continuous integration/continuous deployment (CI/CD), and containerization. It explores the integration of serverless architectures with Function as a Service (FaaS) and Infrastructure as a Service (IaaS), highlighting the challenges and solutions in their hybrid implementation. The study also delves into the role of Artificial Intelligence (AI) and Machine Learning (ML) in fostering predictive and self-healing cloud systems. Furthermore, it addresses the complexities introduced by multi-cloud configurations and the management tools like Kubernetes and Terraform that aid in their orchestration. By analyzing these technologies, the paper offers insights into future directions and research opportunities in cloud infrastructure automation.​