The overarching objective of 6G-TWIN is to provide the foundation for the design, implementation and validation of an AI-native reference architecture for 6G systems that incorporates Network Digital Twins (NDT) as a core mechanism for the end-to-end, real-time optimisation, management and control of highly dynamic and complex network scenarios. To achieve this objective, 6G-TWIN will deliver methods, modelling and simulation solutions for the definition, creation and management of multi-layered virtual representations of future 6G systems, where heterogeneous domains (i.e., edge, fog and cloud) and communication technologies (e.g., cellular, optical and Non-Terrestrial Networks (NTN)) coexist. The project solutions will be demonstrated in two complementary use cases addressing mobility and energy-efficiency challenges, aligned with the expected use cases of 6G and the Key Performance Indicators (KPI) defined in previously funded projects (including SNS JU STREAM-C/D-2022). Finally, the participation of Small and Medium-sized Enterprises (SMEs) will ensure that the 6G-TWIN consortium pays particular attention to the replication, reengineering and exploitation of the project outcomes, regularly aligning the requirements of standardisation bodies with predicted market needs.

There is a strong upcoming need for communication and beyond technology on the 2030 horizon, with the transformations having been set in motion by 5G, and increasing expectations in society, accelerated by advancements in enabling technology, and moving toward new services and use cases. To address the demanding and diverse needs of the anticipated use cases, 6G networks must be highly programmable, exceedingly adaptable, and efficient. Nevertheless, the additional level of efficiency, programmability and flexibility will come at the expense of increasing complexity in managing and operating 6G networks. To bring this complexity under control, a paradigm shift toward complete automation of network and service management is required. However, a significant obstacle to full automation is the protection of the network services, infrastructure and data against possible cybersecurity risks introduced by the unheard-of expansion of the 6G threat landscape. ROBUST-6G aims to address these cybersecurity risks by 1) providing fundamental contributions to the development of data-driven, AI/ML-based security solutions to meet the new concerns posed by the dynamic nature of the future cyber-physical continuum 2) implementing fully autonomous zero-touch security management functionalities 3) exposing security functionalities to verticals and providing necessary data management 4) protecting AI/ML systems from security attacks and ensuring privacy of individuals whose data is used in the AI-driven systems. 5) providing secure, privacy-preserving and robust distributed intelligence with transparency enhancements by elaborating the explainability in AI/ML 6) achieving energy efficient 6G network design with green and sustainable AI methodologies 7) leveraging different sources of information, ranging from sensing, positioning to authentication, and advanced AI/ML methodologies for detection and mitigation of physical layer attacks and threats.

VERGE will tackle evolution of edge computing from three perspectives: “Edge for AI”, “AI for Edge” and security, privacy and trustworthiness of AI for Edge. “Edge for AI” defines a flexible, modular and converged Edge platform that is ready to support distributed AI at the edge. This is achieved by unifying lifecycle management and closed-loop automation for cloud-native applications, MEC and network services, while fully exploiting multi-core and multi-accelerator capabilities for ultra-high computational performance. “AI for Edge” enables dynamic function placement by managing and orchestrating the underlying physical, network, and compute resources. Application-specific network and computational KPIs will be assured in an efficient and collision-free manner, taking Edge resource constraints in to account. Security, privacy and trustworthiness of AI for Edge are addressed to ensure security of the AI-based models against adversarial attacks, privacy of data and models, and transparency in training and execution by providing explanations for model decisions improving trust in models. VERGE will verify the three perspectives through delivery of 7 demonstrations across two use cases - XR-driven Edge-enabled industrial B5G applications across two separate Arçelik sites in Turkey, and Edge-assisted Autonomous Tram operation in Florence. VERGE will disseminate results to academia, industry and the wider stakeholder community through liaisons and contributions to relevant standardization bodies and open sources, a series of demonstrations showing progression through TRLs and by creating an open dataspace for enabling public access to the datasets generated by the project.

The fifth generation of wireless technology (5G) has arrived and is being rolled out globally. First industrial sectors such as manufacturing are testing the capabilities of 5G showing great potential for ubiquitous connectivity. With the sixth generation (6G), wireless communication will bring new features, improved performance, and functional benefits to several industrial sectors. The TARGET-X project envisions accelerating the digital transformation of key verticals: energy, construction, automotive, and manufacturing using large-scale trials in multiple testbeds. By demonstrating, validating, and evaluating the potential of 5G/6G in real environments, the most advanced 5G/6G technologies such as real-time communication, localization, self-description, digital twinning, and sensor-network data fusion can be tested and evaluated. The focus of the evaluation is on KPIs and especially KVIs, such as sustainability, safety, security, and privacy. Based on these KVIs, new business models and a methodological assessment framework for economic and societal evaluation will be developed. The development of the solutions will be supported and guided by the TARGET-X community, a network of SMEs, IT- and OT-partners, and up to 100 FSTP third parties, bringing together a strong consortium with SMEs and innovation drivers. To reach TARGET-X's goals, a selection of use cases will be established for all verticals in the existing 5G testbeds. New 5G/6G features will be developed and integrated into the testbeds and validated in evolved use cases. The FTSP projects will both deliver new use cases and technical contributions. A large number of FTPS participants will strengthen the 5G/6G ecosystem. Results of the project will be discussed with 6G-SNS projects and used for standardization, also in the different verticals.

Over the past decades the mobile communications has evolved over the different generations to the current 5G, and transformed into a fundamental infrastructure that supports digital demands from all industry sectors. However, 5G systems are expected to fall short on meeting the anticipated stringent performance requirements for the new generation of real time mission-critical applications. In view of that, DESIRE6G will design and develop novel zero-touch control, management, and orchestration platform, with native integration of AI, to support eXtreme URLLC application requirements. DESIRE6G will re-architect mobile networks through a) its intent-based control and end-to-end orchestration that targets to achieve near real time autonomic networking; and b) a cloud-native unified programmable data plane layer supporting multi-tenancy. The latter will be supported by a generic hardware abstraction layer designed for heterogeneous systems. Flexible composition of modular micro-services for slice specific implementations and flexible function placement depending on HW requirements will enable granular use case instantiation and service level assurance with minimum resource consumption and maximum energy efficiency. The DESIRE6G data, control, management, and orchestration plane is supported by a pervasive monitoring system, extending from the network to the user equipment or IoT terminal. DESIRE6G will employ distributed ledger technology to support a) dynamic federation for services across of multiple administrative domains and b) infrastructure-agnostic software security. Finally, DESIRE6G will enable communication-, and energy- efficient distributed AI, at the network edge, while considering application-level requirements and resource constraints. The proposed innovations will be validated employing a VR/AR/MR and a Digital Twin application at two distinct experimental sites.