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

Rut Palmero
Javier Nieto
Funding Program
H2020 h2020
Project Date

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 them superior data analytics capabilities to implement smart and autonomous control applications. The project will validate its results on a smart city use case in the city of Modena.

Our role

The Edge Computing Unit team participates in the development of cloud computing services capable of guaranteeing the “soft real-time” constraints imposed on data operations and analytics tasks. This kind of guarantee is critical for the CLASS high-performance computing platform, which relies on cloud computing resources to run analytics tasks that are not engaged in “hard real-time” (i.e. safety-critical) functions. The NG Cloud is taking a Quality of Service (QoS) approach to ensure the output of these non-critical data operations and analytics tasks are available at the right time.

In addition, the APC & Big Data Unit develops Deep Learning algorithms to process images and videos coming from the city and cars to recognize objects as needed by the cars, with real-time stream processing and deployment.