Multivariate Analysis of Big Data in Software Defined Networks

Project description

A big boost for internet functionality

The amount of data flowing through the Internet is growing quickly and we urgently need new ways to manage, process and analyse it. Software Defined Networking (SDN) has emerged as an interesting approach to handle massive tons of data efficiently, offering programmability in network functionalities. Still, managing an SDN framework is challenging. Big Data analysis techniques can be useful in the identification and troubleshooting of SDN problems, and the optimisation of network performance. The EU-funded MAD-SDN project proposes an approach based on multivariate big data analysis (MBDA) for network monitoring, troubleshooting and traffic classification. The pioneering federated learning approach by Google will be used for distributed data analysis problems.

Fields of science

• natural sciences › computer and information sciences › software
• natural sciences › computer and information sciences › internet
• natural sciences › computer and information sciences › data science › big data

Programme(s)

• H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility

Topic(s)

• MSCA-IF-2019 - Individual Fellowships

Call for proposal

H2020-MSCA-IF-2019
See other projects for this call

Funding Scheme

MSCA-IF-EF-ST - Standard EF

Coordinator

UNIVERSIDAD DE GRANADA

Address

Cuesta Del Hospicio Sn
18071 Granada
Spain

Activity type

Higher or Secondary Education Establishments

EU contribution

€ 172 932,48