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 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, 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 adopting


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


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


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



Project Type



Grant Agreement Number


Project Coordinator

Barcelona Supercomputing Center (BSC)


36 months

Number of Partners


Project Cost


Funding from the EC


Start Date

1st January 2018

End Date

31st December 2020