Abstract
The primary objective of the AINET-ANTILLAS Celtic-Next research program is to accelerate digital transformation in Europe by intelligent and secure network automation.
Automation will occur in many domains like mobile networks, optical networks, smart cities, robotic transportation, IoT and next-generation industries. The MEC (Multi-Access Edge Computing) and IoT markets are expanding rapidly with the emergence of new applications and technologies. As a result, resources for data storage and processing will be distributed and shared among a variety of users and applications.
Control and optimisation of the underlying networks in terms of resources, latency and security are complex tasks requiring intelligent automation. AINET-ANTILLAS will work towards fully autonomous network operation by applying AI/ML enhanced end-to-end automation at both network and services levels. Moreover, the project aspires to be the turning point towards intense automation of MEC powered IoT cybersecurity, as well as for public safety related security. AINET-ANTILLAS concentrates on applying these technologies to automotive / teleoperated driving, manufacturing industry, public safety, and public utility businesses.
At the same time, the current cloud infrastructure is not adequate to serve the transformation’s requirements. Three technologies can come together to shape new, flexible, and cyber resilient services: 5G, edge-centric compute & artificial intelligence. AINET-ANTILLAS will contribute to cyber-resilient intelligent network automation from the edge to the core through the FOG, and from the services to the physical resources, for end users, machine-to-machine and IoT networks. The goal is to provide enablers and solutions for high-performance services deployed and operated at the network edge or in the cloud. To manage complexity and ensure cybersecurity, artificial intelligence will be harnessed to complement traditional optimisation algorithms. To complete the overall picture, monitoring techniques and methods to minimize energy consumption and optimise the network resources are advanced.
