CODECO is a cognitive, cross-layer and highly adaptive Edge-Cloud management framework with a unique orchestration approach that provides support for data management and governance decentralised data workflow; dynamic offloading of computation and computation status; and adaptive networking services (TRL5). In the core of the CODECO framework are privacy preserving decentralised learning mechanisms to i) reduce latency and power consumption from the far Edge to Cloud; ii) adjust the computation in real-time to available Edge-Cloud constraints; iii) adjust running services into the needs of the application, the data sources, the surrounding context; iv) benefit from a flexible networking infrastructure that adapts to the needs of active services; and v) democratize the technology to a faster market adoption of the toolkit, as well as products and services derived from it. CODECO proposes the following assets: i) A1: Open, cognitive toolkits and smart Apps, integrating the elastic and advanced concepts to manage, in a smart and flexible way, containerized applications across Edge and Cloud (dynamic cluster and multi-cluster environment; ii) A2: A developer-oriented open-source software repository, to be available in an early stage of the project, thus allowing for early exploitation of initial, advanced results and a better adaptation throughout the project lifetime; iii) A3: Training tools, to support the development of services based on the CODECO framework; iv) A4: Use-cases across 4 domains (Smart Cities, Energy, Manufacturing, Smar Buildings), as the basis for experimentation and demonstrations; v) A5: a Research and Innovation community engagement programme, based on the different use-cases and including the different CODECO stakeholders; vi) A6: CODECO integration into the large-scale EdgeNet , experimental infrastructure, to assist in the building of experimentation and novel concepts by the research community.

The ever-growing resource needs of modern-day applications regarding guaranteed low latency and the massive data transfer rate are constantly pushing the boundaries of technologies and requiring a paradigm shift. To cater for these escalating resource needs, modern IT computing platforms have evolved beyond the more traditional central cloud/DC with bleeding-edge processing powers and high-capacity networking infrastructure to extend their coverage all the way to the network edge, which may also include the far-edge nowadays. This creates a new paradigm called cloud edge computing continuum (CECC), whereby the services span from core cloud to edge and far edge. To efficiently manage and continuously optimize resources through this new model using the CECC approach, we propose an Agile and Cognitive Cloud-edge Continuum (AC3) management framework. This framework will play a critical role in providing scalability, agility, effectiveness, and dynamicity in service delivery over the CECC infrastructure. AC3 will offer a common and secure federated platform that manages data source, CECC resources, and application behaviour in a unified and harmonized manner to ensure the desired SLA and save energy consumption. Moreover, the AC3 platform can adapt to a different context and events happening in the network, such as lack of resources, data deluge, or mobility of data source, by managing (i.e., deploying or migrating) micro-services across CECC infrastructures. AC3 will leverage AI, ML, and semantic and context awareness algorithms to provide an efficient life cycle management system of services, data sources, and CECC resources for ensuring low response time and high data rate while saving energy consumption.

Q-FENCE is a transformative initiative aimed at securing tomorrow’s digital infrastructure with quantum-resistant cryptography. In response to the rising threats posed by quantum computing, Q-FENCE develops a robust hybrid framework integrating classical, quantum, and post-quantum cryptographic techniques. Utilizing innovative approaches such as Ring-LWE, Module-LWE, Quantum Random Number Generators, and hardware-accelerated primitives, the project establishes a dual-layer security model that fortifies data protection across diverse infrastructures. Leveraging hardware-accelerated primitives and energy-efficient protocols, Q-FENCE ensures quantum resilience while addressing critical challenges such as seamless integration with legacy systems, regulatory compliance, and scalable deployment. By addressing key challenges like legacy system integration, interoperability, and regulatory compliance, it ensures a phased and seamless adoption across sectors including finance, healthcare, IoT, satellite and digital networks. Through sector-specific demonstrators, best-practice guidelines, and collaboration with EU policymakers, Q-FENCE bridges the gap between theoretical advancements and real-world applications, fostering digital sovereignty and resilience. Positioned as a critical player in the quantum-ready future, Q-FENCE not only safeguards sensitive data but also empowers stakeholders with practical, scalable, and innovative post-quantum solutions.

CONNECT addresses the convergence of security and safety in CCAM by assessing dynamic trust relationships and defining a trust reasoning framework based on which involved entities can establish trust for cooperatively executing safety-critical functions. This will enable both a) cyber-secure data sharing between data sources in the CCAM ecosystem that had no or insufficient pre-existing trust relationship, and b) outsourcing tasks to the MEC and cloud in a trustworthy way. Beyond the needs of functional safety, trustworthiness management should be included in CCAM’s security functionality solution for verifying trustworthiness of transmitting stations and infrastructure. CONNECT will build upon and expand the Zero Trust concept to tackle the issue of how to bootstrap vertical trust from the application, the execution environment and device hardware from the vehicle up to MEC and cloud environments. This includes measuring the system when instantiating network functions and determining the integrity and origin of software. Trusted Execution Environments (TEEs), as sw- or hw-based security elements, will be essential to establish a verifiable chain of trust throughout the entire application stack of the host vehicle, as well as protecting data in transit, at rest and in use. By coupling the Zero Trust security principle with the need of “Never Trust, Always Verify”, CONNECT bootstraps vertical trust for all users, devices and systems in the CCAM ecosystem by enabling continuous authorization and authentication prior to be granted access to data or resources. Through TEE-enabled “Chip-to-Cloud" assurances and verifiable chain of trust, CONNECT reaches its full potential: not only does it mitigates risks stemming from the Zero Trust CCAM environment but also ensures resilience. This can make CONNECT the cornerstone of future smart transportation as it will usher new levels of safety and connectivity and bring vehicles even close to autonomy.