About

We work towards an efficiently distribution of big-data workloads along the compute continuum (from edge to cloud) in a complete transparent way, while providing sound real-time guarantees on end-to-end data analytics responses.

Big data analytics are being applied to a wide range of applications domains, including those in charge of controlling critical real-time systems, challenging the need not only to efficiently processing extreme amounts of complex data, but also processing it in real-time.

CLASS developed 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 have been demonstrated on a real smart-city use case in the City of Modena, 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.

Meet the Partners

CLASS aims to adopt

1

Innovative parallel and distributed programming models and architectures from the high-performance domain.

2

Timing analysis methods and energy efficient parallel architectures from the real-time embedded domain.

3

Advanced data analytics platforms and programming models from the big-data domain.

Project Name

Edge and Cloud Computation: a Highly Distributed Software for Big Data Analytics

Acronym

CLASS

Project Type

RIA

 

Grant Agreement Number

780622

Project Coordinator

Barcelona Supercomputing Center (BSC)

Duration

42 months

Number of Partners

6

Project Cost

3,9M€

Funding from the EC

3,9M€

Start Date

1st January 2018

End Date

30th June 2021