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CLASS SIGNED

Edge and CLoud Computation: A Highly Distributed Software Architecture for Big Data AnalyticS

Total Cost €

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EC-Contrib. €

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Partnership

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 CLASS project word cloud

Explore the words cloud of the CLASS project. It provides you a very rough idea of what is the project "CLASS" about.

edge    cars    streams    framework    separately    collect    priorities    software    aggregating    amount    autonomous    compute    assistance    computationally    innovative    smart    incompatible    continuous    complete    implies    driving    flows    efficient    motion    services    urban    time    sound    architectures    vehicles    v2i    designed    complementary    heavy    area    vast    drivers    apparently    advent    background    energy    reactive    extreme    actuators    traffic    tackled    usually    demonstrated    analytics    programming    city    parallel    data    big    heterogeneous    transparent    platforms    featuring    adopting    domains    distributed    equipped    representative    feedback    quick    guarantees    timing    larger    cloud    possibly    developers    performance    sensors    mining    preparing    nowadays    amounts    technological    domain    rest    continuum    distributing    architecture    combine    thorough    sensor    intensive    conflicting    class    infrastructure    cluster    connectivity    models    prototype   

Project "CLASS" data sheet

The following table provides information about the project.

Coordinator
BARCELONA SUPERCOMPUTING CENTER - CENTRO NACIONAL DE SUPERCOMPUTACION 

Organization address
address: Calle Jordi Girona 31
city: BARCELONA
postcode: 8034
website: www.bsc.es

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Spain [ES]
 Project website https://class-project.eu/
 Total cost 3˙900˙802 €
 EC max contribution 3˙900˙802 € (100%)
 Programme 1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
 Code Call H2020-ICT-2017-1
 Funding Scheme RIA
 Starting year 2018
 Duration (year-month-day) from 2018-01-01   to  2020-12-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    BARCELONA SUPERCOMPUTING CENTER - CENTRO NACIONAL DE SUPERCOMPUTACION ES (BARCELONA) coordinator 747˙875.00
2    IBM ISRAEL - SCIENCE AND TECHNOLOGY LTD IL (PETACH TIKVA) participant 973˙190.00
3    MASERATI SPA IT (MODENA) participant 575˙655.00
4    COMUNE DI MODENA IT (MODENA) participant 558˙375.00
5    ATOS SPAIN SA ES (MADRID) participant 553˙541.00
6    UNIVERSITA DEGLI STUDI DI MODENA E REGGIO EMILIA IT (MODENA) participant 492˙166.00

Map

 Project objective

Big data applications processing extreme amounts of complex data are nowadays being integrated with even more challenging requirements such as the need of continuously processing vast amount of information in real-time. Current data analytics systems are usually designed following two conflicting priorities to provide (i) a quick and reactive response (referred to as data-in-motion analysis), possibly in real-time based on continuous data flows; or (ii) a thorough and more computationally intensive feedback (referred to as data-at-rest analysis), which typically implies aggregating more information into larger models. Given the apparently incompatible requirements, these approaches have been tackled separately although they provide complementary capabilities. CLASS aims to develop a novel software architecture to help big data developers to combine data-in-motion and data-at-rest analysis by efficiently distributing data and process mining along the compute continuum (from edge to cloud) in a complete and transparent way, while providing sound real-time guarantees. CLASS aims at adopting (1) innovative distributed architectures from the high-performance domain; (2) timing analysis methods and energy-efficient parallel architectures from the embedded domain; and (3) data analytics platforms and programming models from the big-data domain. The capabilities of the CLASS framework will be demonstrated on a real smart-city use case, featuring a heavy sensor infrastructure to collect real-time data across a wide urban area, and prototype cars equipped with heterogeneous sensors/actuators, V2I connectivity, and cluster support to present the innovative capabilities to drivers. Representative applications for traffic management and advanced driving assistance domains have been selected to efficiently process very large heterogeneous data streams in real-time, providing innovative services while preparing the technological background for the advent of autonomous vehicles

 Deliverables

List of deliverables.
Communication and Dissemination Plan Documents, reports 2019-11-26 15:02:54
First release of the real-time analysis methods and tools on the edge Demonstrators, pilots, prototypes 2019-11-26 15:02:53
Data Management Plan (DMP) Open Research Data Pilot 2019-11-26 15:02:56
First release of the Cloud Data Analytics Service Scalability components Demonstrators, pilots, prototypes 2019-11-26 15:02:54
Advanced multi-workload/multi-tenant performance evaluation tool for big data services Demonstrators, pilots, prototypes 2019-11-26 15:02:53
Initial communication and dissemination report Documents, reports 2019-11-26 15:02:55

Take a look to the deliverables list in detail:  detailed list of CLASS deliverables.

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The information about "CLASS" are provided by the European Opendata Portal: CORDIS opendata.

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