ARTIFICIAL INTELLIGENCE: Sant’Anna SCHOOL TECIP INSTITUTE researchers develop “ARTIFICIAL INTELLIGENCE FOR Network function virtualization” for vodafone data centers

Vodafone and Sant’Anna School TeCIP Istitute (Communication, Information and Perception Technologies) work on the design and development of modern data centers driven by Artificial Intelligence. Artificial Intelligence (AI) is transforming data centers and enabling the transition from manually managed networks to fully autonomic and self-organized networks. The paradigm shift towards virtualized (NFV - Network Function Virtualization) networks will allow more flexibility and provide the option to automate a wide range of management tasks. The “AI for NFV” project is developing a self-organized network management framework through virtualized networks to support 5G technologies and reduce operational expenditures.

The project is supervised by Professor Tommaso Cucinotta of the TeCIP Real-Time Systems Laboratory (RETIS) and Antonino Artale, project manager of the Vodafone Network Virtual Infrastructure Design. Their self-organized network management framework will detect malfunctions in NFV applications through sensors that extract metrics from the network infrastructure with the help of learning dataset.

The project is quite complex due to the amount of data to be analyzed, as well as their high dimensionality, as each physical and virtual machine exposes hundreds of metrics which are continuously monitored. The TECIP is tackling the project exploiting multi-disciplinary competencies coming from multiple laboratories, like the RETIS for the experience in operating systems, virtualization and performance engineering, the PERCRO and ICT-COISP for big-data processing and machine learning, and the INRETE for the design and analysis of next-generation telecommunication networks.

The project adds to the on-going collaborations between the TECIP institute and renowned national and international industrial players, and it constitutes a unique opportunity for researchers of the Sant'Anna to apply and refine their academic methodologies and competencies,  working with real data sets.

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