The current trend for data placement shows a steady shift towards "the cloud". The advent of cloud storage and computation services however comes at the expense of data security and user privacy. To remedy this, customers nowadays call for end-to-end security whereby only end-users and authorized parties have access to their data and no-one else. This is especially true after the outbreak of data breaches and global surveillance programs last year. In the TREDISEC project, we address this problem and we develop systems and techniques which make the cloud a secure and efficient heaven to store data. We plan to step away from a myriad of disconnected security protocols or cryptographic algorithms, and to converge on a single framework where all objectives are met. More specifically, TREDISEC addresses the confidentiality and integrity of outsourced data in the presence of a powerful attacker who controls the entire network. In addition, our proposed security primitives support data compression and data deduplication, while providing the necessary means for cloud providers to efficiently search and process encrypted data. By doing so, TREDISEC aims at creating technology that will impact existing businesses and will generate new profitable business opportunities long after the project is concluded.

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.

Multi-cloud applications refer to applications that dynamically can distribute their components over heterogeneous cloud resources and still hold the functional, business and non-functional properties (NFP) declared in their SLAs. The main objective of the DECIDE action is to provide a new generation of multi-cloud service-based software framework, enabling techniques and mechanisms to design, develop, and dynamically deploy multi-cloud aware applications in an ecosystem of reliable, interoperable, and legal compliant cloud services (DECIDE DevOps Framework). DECIDE will provide a set of architectural patterns and the needed tools (DECIDE ARCHITECT) to develop and operate (following the DevOps approach) multi-cloud aware applications that can be dynamically self-adapted to be re-deployed using the best combination of cloud services. DECIDE will also set up an ecosystem of trusted, interoperable and legally compliant cloud services (ACSmI-Advance Cloud Service meta-Intermediator) and the required mechanisms to register, discover, compose, use and assess them. One of the key innovations of the DECIDE solution relies on the development of the OPTIMUS deployment simulation tool capable of evaluating and optimizing the resulting non-functional characteristics from the user’s perspective considering a set of given cloud resources alternatives. The OPTIMUS deployment simulation tool, together with the continuous deployment supporting tool (DECIDE ADAPT), will provide the most adequate deployment application topology based on a set of users’ requirements automating the provisioning and selection of deployment scripts for multi-cloud applications. Three use cases will be conducted to validate. DECIDE will innovate by tackling with multi-cloud and non-functional aspects and moreover by incorporating a DevOps approach to the whole solution DECIDE outcomes, covering the specific needs of different multi-cloud applications for on-line gaming, e-Health and Network management.

The integration of edge computing, advanced 5G connectivity, and decentralized processing drives the widespread deployment of private edge ecosystems capable to reshape numerous industry sectors. However, unlocking the full potentials of edge-level intelligent management requires concerted efforts in platform development and cross-sector collaboration. COP-PILOT, develops a Collaborative Open Platform framework geared towards orchestrating end-to-end services across diverse industry domains. In crafting an open platform, COP-PILOT provides a flexible solution designed to effectively manage various industry sectors while ensuring robust security, automation, and intelligence features. Regarding interoperability, the framework seamlessly integrates with underlying technologies, ranging from IoT platforms to core infrastructure, facilitating collaboration across the compute continuum. Furthermore, COP-PILOT empowers the development of advanced cross-sector applications by offering support for cutting-edge network services, thereby enabling heightened security, resource management, and automation capabilities. The implementation strategy revolves around two primary directions: enabling platform implementation and real environment integration. For the former, COP-PILOT adopts a modular orchestration approach, simplifying the onboarding of complex applications through a user-friendly generative AI interface. This approach includes integration with multi-tiered data processing, policy-driven optimization, and dynamic reasoning capabilities, ensuring alignment with prevailing industry standards. In terms of real environment integration, the platform is deployed across four large piloting clusters, addressing a diverse array of edge paradigms. These use cases span across energy, smart city, agriculture, and industrial manufacturing sectors, fostering the development of cross-sector applications in mobility, logistics, and resource management.