Periodic Reporting for period 1 - 6G-CLOUD (Service-oriented 6G network architecture for distributed, intelligent, and sustainable cloud-native communication systems)
Periodo di rendicontazione: 2024-01-01 al 2024-12-31
The 6G-Cloud project seeks to address the inherent limitations of current 5G systems and meet rapidly evolving connectivity demands. Building on the innovative paradigms of 5G, such as service-based architecture, and dis-aggregated RAN, the project extends cloudification to all networking domains, including radio, core, edge, and application layers. This approach envisions an AI-native, cloud-friendly system architecture where network functions from different 6G segments are flexibly composed and dynamically orchestrated in a hybrid cloud environment. 6G-Cloud will focus on i) creating an AI-native 6G system architecture based on a cloud continuum; ii) developing AI-driven management frameworks and business interfaces for multiple stakeholders; iii) establishing an AI/ML framework for native-AI support in 6G; iv) supporting the 6G "network-of-networks" through service-oriented network design. The project addresses technical challenges such as the static nature of 5G management platforms and the lack of integrated multi-domain orchestration while emphasizing scalability, resilience, security, and energy efficiency to satisfy both user and operator requirements. The concept will be validated by three proofs-of-concepts and promoted through 6G architectural standardization work and open-source projects to reach maximum impact. The project aims to contribute to an open, intelligent, cloud-native, sustainable, and secure 6G system, aligning with Europe’s 6G vision to enhance leadership in next-generation mobile network technologies and services.
In the first year of the project, the consortium worked towards defining the requirements for the 6G-Cloud system design and architectural design principles based on 6G use cases and their requirements. Additionally, the consortium carried out an analysis of key value indicators (KVI) and key performance indicators (KPI) to be considered in 6G-Cloud system architecture design, validation, and performance evaluation, to better understand their impacts in 6G use cases.
The 6G-Cloud architecture design principles emphasize flexibility and dynamic deployment to adapt to varying connectivity needs, infrastructure resources, and optimization goals. It enables novel network concepts through service-based radio access networks (RAN), RAN-Core convergence, and enhanced service delivery, emphasizing reduced latency, scalability, energy efficiency, and sustainability. The design integrates cloud-native principles with distributed, programmable control, ensuring seamless orchestration across hybrid environments. Native artificial intelligence (AI)/machine learning (ML) support enhances performance, cost-efficiency, and energy optimization while managing the complexity of heterogeneous, multi-vendor networks. The cloud continuum concept underpins the architecture, enabling the dynamic allocation of compute/storage resources across public and private clouds. This unifies service-oriented RAN and core functions for unprecedented adaptability, resource utilization, and service innovation, supporting emerging 6G applications.
The 6G-Cloud architecture design principles emphasize flexibility and dynamic deployment to adapt to varying connectivity needs, infrastructure resources, and optimization goals. It enables novel network concepts through service-based radio access networks (RAN), RAN-Core convergence, and enhanced service delivery, emphasizing reduced latency, scalability, energy efficiency, and sustainability. The design integrates cloud-native principles with distributed, programmable control, ensuring seamless orchestration across hybrid environments. Native artificial intelligence (AI)/machine learning (ML) support enhances performance, cost-efficiency, and energy optimization while managing the complexity of heterogeneous, multi-vendor networks. The cloud continuum concept underpins the architecture, enabling the dynamic allocation of compute/storage resources across public and private clouds. This unifies service-oriented RAN and core functions for unprecedented adaptability, resource utilization, and service innovation, supporting emerging 6G applications.
As two major results from the first year, 6G-Cloud has developed an orchestration framework and an initial service-based RAN architecture. The orchestration framework uses a separation-of-concern approach, splitting the system into frameworks that can be independently updated. The cloud continuum framework (CCF) manages resources from multiple providers, enabling dynamic resource pooling for network services. The management and orchestration framework (MOF) works with CCF to manage cloud resources and network functions. The AI/ML Framework (AIMLF) monitors and orchestrates AI/ML-driven functions using a network digital twin (NDT) to enhance decision-making. These frameworks offer a flexible, scalable, and intelligent base for 6G networks.
The service-based RAN architecture introduces a control fabric to enhance performance in dis-aggregated RAN. It integrates with service-based architecture (SBA) in domains like 5G core and extreme edge, supporting end-to-end services with specific quality of service (QoS) needs. A logical message bus allows efficient communication between network functions (NF) and RAN apps. Non-SBA NFs, crucial for user data flows, remain outside the SBA to meet latency demands. These NFs translate SBA APIs into infrastructure commands and offer control endpoints for flexible configurations, such as network slicing. The architecture is adaptable for future 6G applications, including AI/ML-controlled radio units.
The service-based RAN architecture introduces a control fabric to enhance performance in dis-aggregated RAN. It integrates with service-based architecture (SBA) in domains like 5G core and extreme edge, supporting end-to-end services with specific quality of service (QoS) needs. A logical message bus allows efficient communication between network functions (NF) and RAN apps. Non-SBA NFs, crucial for user data flows, remain outside the SBA to meet latency demands. These NFs translate SBA APIs into infrastructure commands and offer control endpoints for flexible configurations, such as network slicing. The architecture is adaptable for future 6G applications, including AI/ML-controlled radio units.