Network Slicing (NS) is an essential technique extensively used in 5G networks computing strategies, mobile edge computing, mobile cloud computing, and verticals like the Internet of Vehicles and industrial IoT, among others. NS is foreseen as one of the leading enablers for 6G futuristic and highly demanding applications since it allows the optimization and customization of scarce and disputed resources among dynamic, demanding clients with highly distinct application requirements. Various standardization organizations, like 3GPP's proposal for new generation networks and state-of-the-art 5G/6G research projects, are proposing new NS architectures. However, new NS architectures have to deal with an extensive range of requirements that inherently result in having NS architecture proposals typically fulfilling the needs of specific sets of domains with commonalities. The Slicing Future Internet Infrastructures (SFI2) architecture proposal explores the gap resulting from the diversity of NS architectures target domains by proposing a new NS reference architecture with a defined focus on integrating experimental networks and enhancing the NS architecture with Machine Learning (ML) native optimizations, energy-efficient slicing, and slicing-tailored security functionalities. The SFI2 architectural main contribution includes the utilization of the slice-as-a-service paradigm for end-to-end orchestration of resources across multi-domains and multi-technology experimental networks. In addition, the SFI2 reference architecture instantiations will enhance the multi-domain and multi-technology integrated experimental network deployment with native ML optimization, energy-efficient aware slicing, and slicing-tailored security functionalities for the practical domain.

翻译：网络切片(NS)是5G网络计算策略、移动边缘计算、移动云计算以及车联网、工业物联网等垂直领域中广泛使用的关键技术。鉴于NS能够优化和定制稀缺且存在争议的资源，以满足具有高度差异化应用需求的动态、苛刻客户，它被视为6G未来高要求应用的主要使能技术之一。包括3GPP新一代网络提案及前沿5G/6G研究项目在内的众多标准化组织，正在提出新的NS架构。然而，新的NS架构必须应对广泛的需求，这导致NS架构提案通常仅能满足具有共性的特定领域集合的需求。切片未来互联网基础设施(SFI2)架构提案旨在探索不同NS架构目标领域多样性所导致的差距，提出了一种新型NS参考架构，其核心聚焦于集成实验网络，并通过原生机器学习(ML)优化、节能切片以及切片定制安全功能来增强NS架构。SFI2架构的主要贡献包括采用切片即服务范式，实现跨多域及多技术实验网络的端到端资源编排。此外，SFI2参考架构的实例化将通过原生ML优化、节能感知切片及切片定制安全功能，增强面向实际应用领域部署的多域、多技术集成实验网络。