Taking into consideration the continued erratic development of the worldwide COVID-19 pandemic and the accompanying restrictions of worldwide travelling as well as the safety and health of the DATE community, the Organising Committees decided to host DATE 2021 as a virtual conference in early February 2021. Unfortunately, the current situation does not allow a face-to-face conference in Grenoble, France.

The Organising Committees are working intensively to create a virtual conference that gives as much of a real conference atmosphere as possible. Industry Partners will soon be informed about virtual exhibition and sponsorship opportunities.

Updated information will always be available on this page.

CLASS. Edge and Cloud Computation: A Highly Distributed Software for Big Data Analytics

CLASS. Edge and Cloud Computation: A Highly Distributed Software for Big Data Analytics
CLASS. Edge and Cloud Computation: A Highly Distributed Software for Big Data Analytics
Booth
EP 2
Contact Person
Eduardo Quiñones
Location

Barcelona Supercomputing Center (BSC)
Jordi Girona 29 (Nexus II Building)
08034 Barcelona Barcelona
Spain

CLASS aims to develop a novel software architecture framework to help big data developers to efficiently distributing data analytics workloads along the compute continuum (from edge to cloud) in a complete and transparent way, while providing sound real-time guarantees. This ability opens the door to the use of big data into critical real-time systems, providing to them superior data analytics capabilities to implement more intelligent and autonomous control applications.

The capabilities of the CLASS framework will be demonstrated on a real smart-city use case in the City of Modena (Italy), featuring a heavy sensor infrastructure to collect real-time data across a wide urban area, and three connected vehicles equipped with heterogeneous sensors/actuators and V2X connectivity to enhance the driving experience.

The CLASS project has received funding from the European Union’s Horizon 2020 research and innovation programme under the grant agreement No 780622