About
Concept & Methodology
Concept
FLECON-6G proposes a novel 6G blueprint reference architecture driven by distributed, modular, open, collaborative, trustworthy frameworks and multi-layer NDTs, introducing several technical innovations:
At the Business Support System (BSS) Level
Smart Marketplace:
This offers Network Infrastructure as a Service (NIaaS) to verticals and application developers. It is extended with a wide set of NDTs, trustworthy AI, security tools, and network services, which can be discovered and consumed on-demand by vertical applications and upper layers.
At the Control, Management and Orchestration Level
Network of Networks (NoN) Collaborative Framework:
Ensures flexible, scalable, dynamic and efficient composition of 6G networks of networks and their improved automation, optimised and sustainable operation.
Intelligence Layer:
implements the composition, management and orchestration logic of the NoN-Collaborative Framework.
At the Data Plane Level
Accelerated Programmable
Data Plane:
Provides a unified programmable interface to applications and services while implementing lower-level accelerated techniques for improved traffic and service performance offloading.
Methodology
FLECON-6G adopts an iterative and incremental development approach, integrating advanced technologies to produce the next generation of 6G architecture. It applies a dynamic design, implementation, testing, and usage process, running concurrently with relevant environment validations of the technological components. FLECON-6G expects significant feedback and adjustments, which will aid in meeting the target KPIs and KVIs through ongoing refinements influenced by experiments. Open to incorporating emerging technologies and responsive to new requirements, FLECON-6G prioritises modular design to minimise interdependencies among components.
FLECON-6G will be executed over contiguous and sequentially aligned phases focusing on the requirements analysis, the definition of UCs scenarios and methodologies, the design of the architecture, the development of the system’s building blocks and their integration, technology validation through the PoCs, and impact maximisation activities. These phases aim to provide and improve a consolidated set of results, and therefore, the following approaches will be used to enable faster software development:
Service-oriented methodology for the design approach.
An agile approach for the development of the FLECON-6G software components.
Machine Learning Operations (MLOps) methodology for developing the FLECON-6G AI/Machine Learning (ML) algorithms.
Theoretical considerations, simulation, and experimentation in a lab and an industrial environment for validating the FLECON-6G concept and technologies.