Started at: 01-01-2023
Ends on: 31-12-2025
Budget: € 5 999 798
Areas: Software Networks (SN) & Mobile Wireless Internet (MWI)
The overall aim of NANCY is to introduce a secure and intelligent architecture for the wireless network beyond the fifth generation (B5G). Leveraging AI and blockchain, NANCY enables secure and intelligent resource management, flexible networking, and orchestration. In this direction, novel architectures, namely point-to-point (P2P) connectivity for device-to-device connectivity, mesh networking, and relay-based communications, as well as protocols for medium access, mobility management, and resource allocation, will be designed. These architectures and protocols will make the most by jointly optimizing the midhaul and fronthaul. This is expected to enable truly distributed intelligence and transform the network to a low-power computer. Likewise, by following a holistic optimization approach and leveraging the developments in blockchain, NANCY aims to support E2E personalized, multi-tenant and perpetual protection.
Within the project, the i2CAT Foundation has an active role in Work Package 3 – “NANCY Architecture & Orchestration”, which main objective is to provide the overall design of the NANCY architecture based on three pillars:
i2CAT leads Task 3.4 – AI virtualiser for underutilized computational and communication resource exploitation. Within this task, researchers will deliver the NANCY AI virtualiser, which is responsible for identifying the computational resources required by a specific task and making the appropriate offloading decisions. It enables the exploitation of unutilized computational resources found throughout the NANCY edge-to-cloud continuum.
NANCY takes advantage of technologies like slicing, NG-SDN, and NFV and intelligently combines them with ML techniques that can detect the availability patterns of edge and mobile nodes to increase the resource manager’s flexibility. Finally, i2CAT will lead the research on the AI virtualiser for resource exploitation.
Additionally, in Task 4.2, “Resource elasticity enabling techniques”, i2CAT is developing a forwarding engine for Sub6 enhanced Integrated Access and Backhaul (IAB) networks that combines an offline path selection heuristic with online Deep Reinforcement Learning (DRL) to allocate traffic flows according to different traffic engineering criteria.
Finally, to validate, test, and demonstrate the feasibility, applicability, effectiveness, and efficiency of the NANCY network in diverse wireless environments and identify its limitations, researchers will deliver three demonstrators (outdoor testbeds), one for each usage scenario. In particular, i2CAT will contribute to the Spanish outdoor testbed, focusing on mobility management, orchestration, resilience/security, and privacy.
The resulting scientific, economic/technological and social impact expected from NANCY includes:
Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the Smart Networks and Services Joint Undertaking as granting authority. Neither the European Union nor the granting authority can be held responsible for them.
NANCY project has received funding from the Smart Networks and Services Joint Undertaking (SNS JU) under the European Union’s Horizon Europe research and innovation programme under Grant Agreement No 101096456