Periodic Reporting for period 1 - MYRTUS (Multi-layer 360° dYnamic orchestration and interopeRable design environmenT for compute-continUum Systems)
Reporting period: 2024-01-01 to 2025-06-30
MYRTUS addresses a key challenge in the cyber-physical systems (CPS), which must operate in dynamic environments but are limited by today’s fragmented edge–fog–cloud infrastructures. Current ecosystems face high latency, inflexibility, energy inefficiency, security gaps, and poor support for legacy systems.
To overcome these issues, MYRTUS envisions a holistic federated computing continuum, seamlessly integrating heterogeneous resources across edge, fog, and cloud. This approach is aligned with EU initiatives such as the Cloud-Edge-IoT Continuum and Gaia-X.
MYRTUS main objective is to create and validate a next-generation continuum platform that makes CPS capable of perceiving, reasoning, adapting, and making trust-driven decisions, through:
Federated multi-layer infrastructures, spanning low-power edge devices to fog and cloud.
MIRTO, an AI-powered orchestration engine for real-time, multi-objective optimization, handling workload (WL) placement and resource customization.
A Design and Programming Environment (DPE) based on open standards (TOSCA, MLIR), enabling seamless cross-platform modeling, simulation, deployment, and verification.
Guided by principles of sustainability, openness, and trust, MYRTUS ensures energy-aware orchestration, portability, support for legacy systems, and adherence to FAIR and open-source principles.
In the short to mid-term, MYRTUS will demonstrate the integration of federated infrastructures in real scenarios, enable dynamic and energy-aware orchestration, and provide a unified open development environment, delivering open-source software/tools aligned with Gaia-X and FAIR principles.
In the long run, MYRTUS aims to impact:
Digital sovereignty, reducing dependency on proprietary platforms.
Innovation acceleration, lowering barriers for SMEs and startups.
Environmental sustainability, via energy-aware optimization and green computing practices.
Societal benefits, improving safety in mobility and health outcomes through advanced CPS applications.
To overcome these issues, MYRTUS envisions a holistic federated computing continuum, seamlessly integrating heterogeneous resources across edge, fog, and cloud. This approach is aligned with EU initiatives such as the Cloud-Edge-IoT Continuum and Gaia-X.
MYRTUS main objective is to create and validate a next-generation continuum platform that makes CPS capable of perceiving, reasoning, adapting, and making trust-driven decisions, through:
Federated multi-layer infrastructures, spanning low-power edge devices to fog and cloud.
MIRTO, an AI-powered orchestration engine for real-time, multi-objective optimization, handling workload (WL) placement and resource customization.
A Design and Programming Environment (DPE) based on open standards (TOSCA, MLIR), enabling seamless cross-platform modeling, simulation, deployment, and verification.
Guided by principles of sustainability, openness, and trust, MYRTUS ensures energy-aware orchestration, portability, support for legacy systems, and adherence to FAIR and open-source principles.
In the short to mid-term, MYRTUS will demonstrate the integration of federated infrastructures in real scenarios, enable dynamic and energy-aware orchestration, and provide a unified open development environment, delivering open-source software/tools aligned with Gaia-X and FAIR principles.
In the long run, MYRTUS aims to impact:
Digital sovereignty, reducing dependency on proprietary platforms.
Innovation acceleration, lowering barriers for SMEs and startups.
Environmental sustainability, via energy-aware optimization and green computing practices.
Societal benefits, improving safety in mobility and health outcomes through advanced CPS applications.
Here are the main activities carried out within the first half of the project
Definition of a multi-Layer reference infrastructure for computing continuum architectures:
Specification and partial integration of a three-tier ecosystem composed of edge (embedded SoCs, and customizable FPGAs-based computing platforms), fog (micro data centers, lightweight nodes, gateways), and cloud.
Alignment of the proposed reference infrastructure with the principles of the EUCEI EUCloudEdgeIoT initiative.
Outline of the design principles and core components of the GAIA-X Trust Framework, focusing on how it enables secure interoperability in federated environments through verifiable and cryptographically protected claims. Preliminary assessment of the GAIA-X Level-1 is in progress, with the intent to derive a set of guidelines for application in MYRTUS compliant environments.
Definition of the 360° MIRTO cognitive orchestration engine: The MIRTO engine implementation is in progress.
Currently all main components and interfaces among them are defined.
The process to achieve WL WL allocation and continuously monitoring and adapting to meet dynamic objectives is defined.
Definition of the DPE: A modular DPE to support the entire development life cycle has been defined and currently the integration is in progress. All the different parts were carefully designed using well-established standards to ensure interoperability and vendor independence.
Progressive Validation via Use Cases: Two real-world use cases have been selected, and are under development, for iterative development and validation:
Smart Mobility (CCAM): Enhancing perception, navigation, and safety in mobility scenarios.
Virtual Telerehabilitation: Enabling adaptive, scalable home-based rehabilitation with mixed human–virtual agent interaction.
Definition of a multi-Layer reference infrastructure for computing continuum architectures:
Specification and partial integration of a three-tier ecosystem composed of edge (embedded SoCs, and customizable FPGAs-based computing platforms), fog (micro data centers, lightweight nodes, gateways), and cloud.
Alignment of the proposed reference infrastructure with the principles of the EUCEI EUCloudEdgeIoT initiative.
Outline of the design principles and core components of the GAIA-X Trust Framework, focusing on how it enables secure interoperability in federated environments through verifiable and cryptographically protected claims. Preliminary assessment of the GAIA-X Level-1 is in progress, with the intent to derive a set of guidelines for application in MYRTUS compliant environments.
Definition of the 360° MIRTO cognitive orchestration engine: The MIRTO engine implementation is in progress.
Currently all main components and interfaces among them are defined.
The process to achieve WL WL allocation and continuously monitoring and adapting to meet dynamic objectives is defined.
Definition of the DPE: A modular DPE to support the entire development life cycle has been defined and currently the integration is in progress. All the different parts were carefully designed using well-established standards to ensure interoperability and vendor independence.
Progressive Validation via Use Cases: Two real-world use cases have been selected, and are under development, for iterative development and validation:
Smart Mobility (CCAM): Enhancing perception, navigation, and safety in mobility scenarios.
Virtual Telerehabilitation: Enabling adaptive, scalable home-based rehabilitation with mixed human–virtual agent interaction.
MYRTUS introduces advancements across its core pillars: the Reference Computing Continuum Infrastructure , MIRTO Cognitive Engine, and DPE , establishing new paradigms for compute-continuum systems.
Reference Infrastructure : MYRTUS redefines distributed computing with a composable, layered edge-fog-cloud continuum, integrating heterogeneous, autonomous, and federated nodes through seamless virtualization mechanisms. Apart from the advancements at the individual node level, including hardware acceleration via HMPSoCs-based platforms and RISC-V, unlike siloed or vendor-locked solutions, MYRTUS ensures strong interoperability, robust three-level security, and AI-optimized energy efficiency, leveraging Liqo, an innovative Kubernetes-based solution, to allow cross-layer virtualization. MYRTUS aligns with EUCEI initiatives, offering a flexible and adaptable foundation for dynamic WLs/resources management.
MIRTO Cognitive Engine: MIRTO significantly advances compute-continuum orchestration through a customizable decentralized strategy driven by distributed cognitive agents. Leveraging autonomic principles, this engine provides intelligence via continuous feedback, learning, and self-adaptation, enabling informed decisions on resource allocation/customization, task scheduling, and system reconfiguration in complex, dynamic environments. Customized management leverages a modular design strategy that allows opt for different AI-powered WL optimization technologies, including swarm-based and deep-reinforcement learning based strategies, expanding optimization drivers beyond existing frameworks, explicitly integrating privacy, security guarantees, and energy efficiency alongside performance.
MYRTUS DPE: MYRTUS DPE revolutionizes software development for computing continuum with end-to-end tooling and interoperable interfaces, overcoming current fragmented toolchains. Built upon OASIS TOSCA and the MLIR framework, it ensures robust, modular, and cross-platform design.
Within this unified framework, tools like Modelio TOSCA Designer, uniquely integrated with ADT Designer for security-by-design threat modeling, enable early-stage application design and high-level exploration and prospectively will also automated code generation for decentralized swarm-based agents and and countermeasures synthesis, largely, simplifying a traditionally manual process. Moreover, the DPE leveraging an MLIR-based compiler supports a diversity of high-level abstraction inputs targeting a plethora of different hardware platforms, including customizable FPGA-based ones, overcoming traditional vendor lock-in.
Reference Infrastructure : MYRTUS redefines distributed computing with a composable, layered edge-fog-cloud continuum, integrating heterogeneous, autonomous, and federated nodes through seamless virtualization mechanisms. Apart from the advancements at the individual node level, including hardware acceleration via HMPSoCs-based platforms and RISC-V, unlike siloed or vendor-locked solutions, MYRTUS ensures strong interoperability, robust three-level security, and AI-optimized energy efficiency, leveraging Liqo, an innovative Kubernetes-based solution, to allow cross-layer virtualization. MYRTUS aligns with EUCEI initiatives, offering a flexible and adaptable foundation for dynamic WLs/resources management.
MIRTO Cognitive Engine: MIRTO significantly advances compute-continuum orchestration through a customizable decentralized strategy driven by distributed cognitive agents. Leveraging autonomic principles, this engine provides intelligence via continuous feedback, learning, and self-adaptation, enabling informed decisions on resource allocation/customization, task scheduling, and system reconfiguration in complex, dynamic environments. Customized management leverages a modular design strategy that allows opt for different AI-powered WL optimization technologies, including swarm-based and deep-reinforcement learning based strategies, expanding optimization drivers beyond existing frameworks, explicitly integrating privacy, security guarantees, and energy efficiency alongside performance.
MYRTUS DPE: MYRTUS DPE revolutionizes software development for computing continuum with end-to-end tooling and interoperable interfaces, overcoming current fragmented toolchains. Built upon OASIS TOSCA and the MLIR framework, it ensures robust, modular, and cross-platform design.
Within this unified framework, tools like Modelio TOSCA Designer, uniquely integrated with ADT Designer for security-by-design threat modeling, enable early-stage application design and high-level exploration and prospectively will also automated code generation for decentralized swarm-based agents and and countermeasures synthesis, largely, simplifying a traditionally manual process. Moreover, the DPE leveraging an MLIR-based compiler supports a diversity of high-level abstraction inputs targeting a plethora of different hardware platforms, including customizable FPGA-based ones, overcoming traditional vendor lock-in.