Distributed Learning for Virtual Network Mgmt

Website

https://ngiatlantic.eu/funded-experiments/distributed-learning-resilient-virtual-network-management-scale

This project aims at investigating and experimenting with algorithmic and system solutions that efficiently allow the distribution of multi-agent network models for self-scaling and resilient Next Generation networks.

ProjectID

NGI-ATLANTIC:OC4-333

Acronym

Additional Info

The presence of new requirements, such as high reliability, zero packet loss, and real-time interaction, posed by data-intensive applications, e.g., augmented/virtual reality, industrial 4.0, or healthcare, exacerbates the need for more performant, scalable, resilient, and self-adapting networks. To support such applications, there is a need to rethink the design of both networks and applications, creating more intelligent and autonomous networks. While AI/ML technologies continue to evolve at a rapid pace, moving from a paradigm of supervised learning towards distributed self-learning requires solving several challenges in the design and deployment of wide-scale networks. Among those challenges, this project plans to tackle:
1. scalability and sustainability of AI/ML models for network management;
2. robustness of learning solutions in practical deployments.
We plan to use existing NSF-funded large-scale virtual network testbeds and, to solve such network management pro