Periodic Reporting for period 1 - FIDAL (Field Trials beyond 5G)
Période du rapport: 2023-01-01 au 2024-06-30
The FIDAL project is dedicated to advancing 5G and laying the groundwork for 6G technologies by promoting collaborative research, open architectures, and large-scale experimentation. It aims to create an inclusive ecosystem where stakeholders can contribute to network innovation, with a focus on interoperability and testing in real-world environments. By integrating high-resolution sensing, geolocation, and wireless technologies, FIDAL seeks to enhance digital services that merge physical and virtual experiences. The project also builds on the 5G Service-Based Architecture by incorporating AI-driven network management, enhanced slicing, and Multi-Access Edge Computing to support new domains like Extended Reality (XR). It addresses challenges such as defining new KPIs and security concerns while providing advanced multi-domain experimentation frameworks that benefit vertical industries and SMEs. A key aspect of FIDAL is the development of Network Applications, standardised and reusable components that simplify service creation across network environments. By fostering cross-industry collaboration and validating technologies in practical contexts, FIDAL aims to accelerate innovation and ensure the successful adoption of 5G advancements while paving the way for 6G.
FIDAL project has carried out significant technical and scientific activities, particularly in relation to the FIDAL project framework, its architecture, and its associated components.:
FIDAL Use Cases: An analysis of each FIDAL use case, including scenarios, workflows, stakeholders, and both functional and non-functional requirements, was completed. The use cases were aligned with Key Performance Indicators (KPIs) and Key Value Indicators (KVIs).
FIDAL Architecture: The architectural design included a comprehensive framework from orchestration levels to data telemetry, AI capabilities, and a repository hosting FIDAL artifacts and results. The architecture diagram was designed to ensure interoperability across components.
Security Framework: A robust security framework was developed, incorporating both traditional and innovative methods. A library of security controls, action plans, and tailored security awareness training were created for different stakeholder profiles.
AIaaS (AI as a Service): AIaaS was developed using telemetry data from 5G testbeds, leveraging machine learning and deep learning techniques to optimize the efficiency of testbeds. This involved creating a data analytics pipeline and deploying multiple predictive APIs for forecasting and network application type prediction.
Maestro Orchestrator: The Maestro component was delivered for service composition and lifecycle management, integrated with various components like the Services Repository, Resource Orchestrator, and Monitoring & Analytics.
Monitoring Analytics: A full version of the Monitoring Analytics platform was developed to capture infrastructure and service metrics, aiding AIaaS workflows and enabling service performance monitoring.
FIDAL Repository Service: The FIDAL Repository Service was developed to manage artifacts such as datasets, container images, and AI training models, with seamless integration for large-scale trial execution.
Testbed Integration: All testbeds were integrated into the FIDAL experimentation framework, exposing interfaces for dynamic service orchestration and data telemetry.
Dry Runs: The first round of dry runs was completed to assess testbed readiness, validating testbed functionalities and their ability to support FIDAL use cases.
Use Case Testing: Each testbed successfully integrated its respective use cases, completing the first series of tests that confirmed the feasibility of the use cases and the capabilities of the testbeds. KPIs and KVIs for the use cases were also validated.
Open Call Launch: The FIDAL Open Call was launched on 15 September 2023 and concluded on 30 December 2023. It aimed to provide access to FIDAL infrastructure for testing new use cases and evaluating innovative solutions.
Promotion and Outreach: The Open Call was widely promoted via various platforms, including the project website, social media, and webinars. Collaborations with organizations such as the European Digital SMEs Alliance further amplified its reach.
Evaluation Process: Proposals were evaluated through a structured, three-step process akin to the Horizon Europe evaluation standards. Successful proposals were onboarded by April 2024.
Helpdesk: A Helpdesk was established to support participants during the application process, addressing both technical and administrative queries, ensuring a smooth onboarding experience.
Second Cycle: Preparations for the second cycle of the Open Call are underway. This involves refining the process for integrating third-party solutions with the FIDAL experimentation framework and ensuring continued engagement from external participants.
FIDAL Use Cases: An analysis of each FIDAL use case, including scenarios, workflows, stakeholders, and both functional and non-functional requirements, was completed. The use cases were aligned with Key Performance Indicators (KPIs) and Key Value Indicators (KVIs).
FIDAL Architecture: The architectural design included a comprehensive framework from orchestration levels to data telemetry, AI capabilities, and a repository hosting FIDAL artifacts and results. The architecture diagram was designed to ensure interoperability across components.
Security Framework: A robust security framework was developed, incorporating both traditional and innovative methods. A library of security controls, action plans, and tailored security awareness training were created for different stakeholder profiles.
AIaaS (AI as a Service): AIaaS was developed using telemetry data from 5G testbeds, leveraging machine learning and deep learning techniques to optimize the efficiency of testbeds. This involved creating a data analytics pipeline and deploying multiple predictive APIs for forecasting and network application type prediction.
Maestro Orchestrator: The Maestro component was delivered for service composition and lifecycle management, integrated with various components like the Services Repository, Resource Orchestrator, and Monitoring & Analytics.
Monitoring Analytics: A full version of the Monitoring Analytics platform was developed to capture infrastructure and service metrics, aiding AIaaS workflows and enabling service performance monitoring.
FIDAL Repository Service: The FIDAL Repository Service was developed to manage artifacts such as datasets, container images, and AI training models, with seamless integration for large-scale trial execution.
Testbed Integration: All testbeds were integrated into the FIDAL experimentation framework, exposing interfaces for dynamic service orchestration and data telemetry.
Dry Runs: The first round of dry runs was completed to assess testbed readiness, validating testbed functionalities and their ability to support FIDAL use cases.
Use Case Testing: Each testbed successfully integrated its respective use cases, completing the first series of tests that confirmed the feasibility of the use cases and the capabilities of the testbeds. KPIs and KVIs for the use cases were also validated.
Open Call Launch: The FIDAL Open Call was launched on 15 September 2023 and concluded on 30 December 2023. It aimed to provide access to FIDAL infrastructure for testing new use cases and evaluating innovative solutions.
Promotion and Outreach: The Open Call was widely promoted via various platforms, including the project website, social media, and webinars. Collaborations with organizations such as the European Digital SMEs Alliance further amplified its reach.
Evaluation Process: Proposals were evaluated through a structured, three-step process akin to the Horizon Europe evaluation standards. Successful proposals were onboarded by April 2024.
Helpdesk: A Helpdesk was established to support participants during the application process, addressing both technical and administrative queries, ensuring a smooth onboarding experience.
Second Cycle: Preparations for the second cycle of the Open Call are underway. This involves refining the process for integrating third-party solutions with the FIDAL experimentation framework and ensuring continued engagement from external participants.
Technical and Scientific Results
The AI as a Service (AIaaS) was integrated into the FIDAL framework, providing predictive analytics and optimization for 5G testbeds using machine learning and deep learning techniques. This ensures that real-time data can be utilized to enhance network performance and resource allocation.
The FIDAL Repository Services were developed to manage datasets, container images, and AI models for reuse, enabling smooth integration for large-scale trials and future open calls.
The Monitoring Analytics platform was delivered and integrated, allowing real-time data collection and analysis from various testbeds. This supports experimentation, service performance monitoring, and optimization of AIaaS workflows.
A comprehensive security framework was established, including a Risk Library, which identified 33 potential risks, combining proactive risk management strategies with tailored security awareness training. This ensures that new technologies introduced in the FIDAL project are secure by design.
The first cycle of the FIDAL Open Call was successfully launched, onboarded, and completed with third-party projects, enhancing external participation in FIDAL trials and providing a platform for wider innovation.
Potential Impacts
1. Innovation in 5G and Beyond:
The development and validation of the FIDAL experimentation framework, especially its integration of AI-driven insights and monitoring, provide a significant boost to the evolution of 5G technologies and beyond. This enhances network automation, optimization, and predictive capabilities, making the framework a critical enabler of advanced telecom applications.
2. Scalability of Trials and Open Access:
The successful integration of testbeds with external use cases demonstrates the scalability and flexibility of the FIDAL framework. This also opens the door for international collaborations, making it easier for third-party developers to experiment on large-scale, real-world 5G test environments.
3. Security as a Key Enabler:
The integration of a strong security framework ensures that the technologies developed under FIDAL can be safely deployed and commercialized, minimizing risks in a highly interconnected ecosystem like 5G.
4. Broader Societal Impact:
The introduction of use cases spanning public safety, media, and industry verticals implies broad societal impact, particularly in sectors that will benefit from real-time, high-bandwidth connectivity and enhanced data analytics capabilities.
The AI as a Service (AIaaS) was integrated into the FIDAL framework, providing predictive analytics and optimization for 5G testbeds using machine learning and deep learning techniques. This ensures that real-time data can be utilized to enhance network performance and resource allocation.
The FIDAL Repository Services were developed to manage datasets, container images, and AI models for reuse, enabling smooth integration for large-scale trials and future open calls.
The Monitoring Analytics platform was delivered and integrated, allowing real-time data collection and analysis from various testbeds. This supports experimentation, service performance monitoring, and optimization of AIaaS workflows.
A comprehensive security framework was established, including a Risk Library, which identified 33 potential risks, combining proactive risk management strategies with tailored security awareness training. This ensures that new technologies introduced in the FIDAL project are secure by design.
The first cycle of the FIDAL Open Call was successfully launched, onboarded, and completed with third-party projects, enhancing external participation in FIDAL trials and providing a platform for wider innovation.
Potential Impacts
1. Innovation in 5G and Beyond:
The development and validation of the FIDAL experimentation framework, especially its integration of AI-driven insights and monitoring, provide a significant boost to the evolution of 5G technologies and beyond. This enhances network automation, optimization, and predictive capabilities, making the framework a critical enabler of advanced telecom applications.
2. Scalability of Trials and Open Access:
The successful integration of testbeds with external use cases demonstrates the scalability and flexibility of the FIDAL framework. This also opens the door for international collaborations, making it easier for third-party developers to experiment on large-scale, real-world 5G test environments.
3. Security as a Key Enabler:
The integration of a strong security framework ensures that the technologies developed under FIDAL can be safely deployed and commercialized, minimizing risks in a highly interconnected ecosystem like 5G.
4. Broader Societal Impact:
The introduction of use cases spanning public safety, media, and industry verticals implies broad societal impact, particularly in sectors that will benefit from real-time, high-bandwidth connectivity and enhanced data analytics capabilities.