## 3 Architectural Approaches
These technologies include AI/ML, blockchain technology for security provision, big data analytics, advanced encryption techniques, and cloud-edge IoT technologies. In [62], the concept of O-RAN is analyzed, as also explained in the previous section. To this end, the basic principles of O-RAN are discussed, which include (i) a disaggregated architecture with modular and standardized interfaces; (ii) cloudification, programmability, and orchestration; and (iii) AI-enabled data-centric closed-loop control and automation. In [63], a native intelligent and security architecture for 6G networks is proposed. In this context, the concept of a super network and multi-bodies is adopted. A super network includes all the main 6G functionalities. Multi-bodies are separate 6G networks with a subset of the central system's functionalities that operate autonomously. The involved NFs communicate with the NFs of the master network to achieve service collaboration and resource optimization. In the same context, in [64], a novel architectural approach is presented that is based on four (4) layers: the resource layer, which is responsible for all data gathering from 6G devices and power allocation. Next, we have the routing and connection layer, which connects all 6G entities. The service-based network function layer is an extension of the SBA approach of 5G networks and can support distributed deployment of services and applications. Finally, the exposure layer can invoke the APIs of other layers to obtain their capabilities. In [65], various use cases are described in the context of 6G networks. These include network-enabled robotic and autonomous systems, multi-sensory extended reality, distributed sensing and communications, and personalized user experience. In [66], the paper investigates the modeling, evaluation, and optimization of DT-based 6G network architecture. To this end, the 6G network architecture is mathematically modelled by intra-domain and inter-domain hypergraphs to characterize the complex changing rules of various elements in the network architecture and their relationships with the supply of services. The inter-domain architecture entropy is introduced to quantify the statistical characteristics of the degree of overlap between network services. In [67], the 6G recursive user plane architecture (6G-RUPA) is described, which is designed to be scalable, flexible, and energy-efficient. A key novelty of 6G networks, as previously mentioned, will be their ability to form a dynamic federation of 6G network operators. Therefore, this federation will allow connected devices to roam freely across different domains with session continuity, without the need to relay traffic through external data networks such as the internet. To this end, this study highlights the appropriate changes that must take place in the user data plane to effectively support device-to-device (D2D) communications without requiring an intermediate data network. The 6G-RUPA approach offers multiple novelties, such as a flexible number of layers, a multilayer quality-of-service (QoS) framework, support for multiple control planes, and AI. In addition to simplifying the user plane network architecture, 6G-RUPA introduces significant improvements to existing verticals through enhanced features like network slicing, edge computing, and support for emerging technologies such as quantum computing and tactile internet. In [68], various technologies are presented with respect to the 6G network, such as DT, AI, distributed ledger technology (DLT), and post-quantum cryptography (PQC). In the same context, in [69], new technological enablers are described, along with current requirements, e.g., new mobility components, CRAN solutions, programmability, and new architecture components for AI. In [70], a self-evolving architectural approach is presented based on self-healing. As also mentioned in the previous section, the extension of the SBA may rely on a similar three-level hierarchical structure, where microservices compose NFs, and the NFs compose the CN.