Periodic Reporting for period 1 - EMPYREAN (EMPYREAN: TRUSTWORTHY, COGNITIVE AND AI-DRIVEN COLLABORATIVE ASSOCIATIONS OF IOT DEVICES AND EDGE RESOURCES FOR DATA PROCESSING)
Reporting period: 2024-02-01 to 2025-07-31
EMPYREAN proposes a new hyper-distributed computing paradigm, based on federations of collaborative and heterogeneous IoT devices and edge/cloud resources across different providers and networks. The federations, namely Associations, operate autonomously and interconnect seamlessly utilizing distributed, cognitive and dynamic AI-enabled decision-making, to balance computing tasks and data inside an Association as well as between Associations in a decentralized, multi-agent manner and across central computing environments, optimizing resources, and providing scalability, resiliency, energy efficiency and QoS.
An Association constitutes a trusted execution environment, while identity and data access management schemes assure controlled data access and confidentiality, utilizing Cluster 3 related outcomes from participating partners. EMPYREAN will also be empowered by automated tools and mechanisms for efficient data processing of ML-workloads and secure distributed edge storage. Developed technologies will provide Associations-native application development and deployment, contributing to the entire application lifecycle and interoperability.
EMPYREAN will provide open and standardized APIs, while utilizing and extending open-source platforms maintained by European companies that participate in the project. EMPYREAN will demonstrate its advanced and innovative capabilities through three well-defined use cases that involve device- and data-rich applications in advanced manufacturing, smart agriculture and warehouse automation, involving AI-driven value extraction of high volume and dynamic IoT data generated at the edge of the network, from multiple sources (e.g. robots). Also, a South Korea based use case in smart factories will further showcase the benefits of the EMPYREAN’s technologies. EMPYREAN will develop its Association-based continuum through synergies with emerging IPCEI initiatives and EU bodies (e.g. GAIA-X, IDSA) where partners participate.
An Association constitutes a trusted execution environment, while identity and data access management schemes assure controlled data access and confidentiality, utilizing Cluster 3 related outcomes from participating partners. EMPYREAN will also be empowered by automated tools and mechanisms for efficient data processing of ML-workloads and secure distributed edge storage. Developed technologies will provide Associations-native application development and deployment, contributing to the entire application lifecycle and interoperability.
EMPYREAN will provide open and standardized APIs, while utilizing and extending open-source platforms maintained by European companies that participate in the project. EMPYREAN will demonstrate its advanced and innovative capabilities through three well-defined use cases that involve device- and data-rich applications in advanced manufacturing, smart agriculture and warehouse automation, involving AI-driven value extraction of high volume and dynamic IoT data generated at the edge of the network, from multiple sources (e.g. robots). Also, a South Korea based use case in smart factories will further showcase the benefits of the EMPYREAN’s technologies. EMPYREAN will develop its Association-based continuum through synergies with emerging IPCEI initiatives and EU bodies (e.g. GAIA-X, IDSA) where partners participate.
During this reporting period, EMPYREAN successfully completed all key objectives, with deliverables finalized.
The project thoroughly examined the latest technologies, standards, and outcomes from relevant EU projects concerning edge-cloud continuum research, providing valuable insights into current technological trends and identifying advancements and challenges to be considered for platform developments. The EMPYREAN concepts were comprehensively defined, with clearly aligned use cases and system requirements to ensure the platform covers operational needs and performance metrics. The analysis of use cases and their correlation with the EMPYREAN architecture provided insights to guide technical developments. A detailed design of the EMPYREAN architecture was delivered, specifying platform components, their interactions, system operation flows, and the roles of different users.
Security, trust, and privacy-preserving data management mechanisms were established, including decentralized identity management, verifiable credentials, secure authentication, fine-grained access control, zero-knowledge proofs, and trusted execution environments. Distributed edge-cloud storage and a software-defined edge interconnect were developed for efficient coordination and low-latency operations. The Analytics Engine architecture was designed with predictive service assurance and REST APIs, while ML-based workload autoscaling advanced resilient CPU, RAM, and GPU scaling.
Multi-objective optimization algorithms, workflow engine extensions, unikernel-based deployment stacks, and analytic-friendly distributed storage systems were developed to enable efficient, secure, and cloud-native execution. Cognitive orchestration mechanisms, including the Aggregator, Registry, and telemetry frameworks, were implemented for autonomous platform management.
Integration, testing, and validation of components has started across EMPYREAN use cases, supported by DevOps pipelines, progressing towards full platform deployment.
The project thoroughly examined the latest technologies, standards, and outcomes from relevant EU projects concerning edge-cloud continuum research, providing valuable insights into current technological trends and identifying advancements and challenges to be considered for platform developments. The EMPYREAN concepts were comprehensively defined, with clearly aligned use cases and system requirements to ensure the platform covers operational needs and performance metrics. The analysis of use cases and their correlation with the EMPYREAN architecture provided insights to guide technical developments. A detailed design of the EMPYREAN architecture was delivered, specifying platform components, their interactions, system operation flows, and the roles of different users.
Security, trust, and privacy-preserving data management mechanisms were established, including decentralized identity management, verifiable credentials, secure authentication, fine-grained access control, zero-knowledge proofs, and trusted execution environments. Distributed edge-cloud storage and a software-defined edge interconnect were developed for efficient coordination and low-latency operations. The Analytics Engine architecture was designed with predictive service assurance and REST APIs, while ML-based workload autoscaling advanced resilient CPU, RAM, and GPU scaling.
Multi-objective optimization algorithms, workflow engine extensions, unikernel-based deployment stacks, and analytic-friendly distributed storage systems were developed to enable efficient, secure, and cloud-native execution. Cognitive orchestration mechanisms, including the Aggregator, Registry, and telemetry frameworks, were implemented for autonomous platform management.
Integration, testing, and validation of components has started across EMPYREAN use cases, supported by DevOps pipelines, progressing towards full platform deployment.
EMPYREAN has achieved significant results beyond the state of the art by advancing secure, privacy-preserving identity and data management, distributed storage, and software-defined edge interconnect architectures for the edge–cloud continuum. The platform introduces novel mechanisms for decentralized identity management, verifiable credentials, zero-knowledge proofs, and trusted execution environments, ensuring data confidentiality and trust. The developed ML-based autoscaling, multi-objective optimization for cloud-native deployment, and unikernel-based execution further enhance efficiency, resilience, and scalability across heterogeneous infrastructures. These outcomes contribute to the next generation of intelligent, autonomous, and secure continuum platforms.
In parallel, EMPYREAN’s dissemination and exploitation activities have supported the potential uptake and impact of the platform. The project website, social media channels, promotional materials, and newsletters have ensured visibility and outreach to relevant stakeholders. Publications and presentations have contributed to knowledge transfer and community engagement. Early business modeling, standardisation, and exploitation activities have been initiated to support commercialisation, internationalisation, and alignment with regulatory and standardisation frameworks, helping to ensure the results can be effectively taken up and applied beyond the project.
In parallel, EMPYREAN’s dissemination and exploitation activities have supported the potential uptake and impact of the platform. The project website, social media channels, promotional materials, and newsletters have ensured visibility and outreach to relevant stakeholders. Publications and presentations have contributed to knowledge transfer and community engagement. Early business modeling, standardisation, and exploitation activities have been initiated to support commercialisation, internationalisation, and alignment with regulatory and standardisation frameworks, helping to ensure the results can be effectively taken up and applied beyond the project.