AI-NET-PROTECT – Providing Resilient & secure networks [Operating on Trusted Equipment] to CriTical infrastructures

The digital transformation has introduced a new paradigm across industries, like healthcare, manufacturing, energy, mobility, entertainment, and others benefiting from new applications and technologies like 5G, cloud and artificial intelligence supporting sustainable development if used transparently and trustworthy.

The Al-NET project is one effort contributing to a European solution in this space, and thereby securing access to critical technology for European industries and people in Europe. Having more control of the needed technology will also help safeguard control of data generated by users and IoT devices in the networks.

The focus of Infosim® inside the Al-NET-PROTECT sub-project is on further extending automated network and service management with a specific scope on telemetry and capacity planning.

Regarding telemetry, topics among others will be the reliability of telemetry based monitoring compared to “classical” pull based monitoring and the handling of potentially delayed or missing monitoring information. A second aspect that will be considered is the scalability in practice of “Push” based mechanisms compared to traditional periodic pulls in very large heterogeneous environments.

For Capacity Planning, Infosim® will among others look into extended methods towards network planning and simulation, involving corresponding visualization of target states, calculation of failure impacts, and more. In this context, Al-based methods are expected to offer additional possibilities e.g. for advanced trend analysis, failure prediction or an ML-supported Root-Cause Analysis based on topology data.

Infosim is looking forward to continue the successful cooperation with other partners from the previous award-winning SENDATE-PLANETS project as well as joining up with new partners.

For further information you can visit the Project Website.

Funding:

BMBF Logo
Federal Ministry of Education and Research