Objective
From edge to cloud, big data analytics is growing fast, and its energy consumption has become a reason of concern for national grids and they generate significant carbon emissions. The GLACIATION project aims to address this issue through energy-efficient data operations. By developing a novel Distributed Knowledge Graph (DKG) that stretches across the edge-core-cloud architecture, reduction in the energy consumption for data processing will be achieved through AI enforced minimal data movement operations. GLACIATION will achieve significant power consumption reduction through optimizing the location where analytics are carried out. The projects Meta Data framework will provide tools that incorporate privacy and trust aspects in the data operations. GLACIATION is demonstrated on three relevant industry settings which benefit from optimized data movement and power consumption reduction. More specifically, GLACIATION use cases cover public-service, manufacturing, and enterprise data analytics.
Fields of science
Programme(s)
Funding Scheme
HORIZON-AG - HORIZON Action Grant Budget-BasedCoordinator
00187 Roma
Italy
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Participants (13)
P31 Ovens
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2273 AB Voorburg
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
30167 Hannover
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1040 Bruxelles
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20122 Milano
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24129 Bergamo
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06410 Biot
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
06410 Biot
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69190 Walldorf
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T12 YN60 Cork
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00143 Roma
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9020 Klagenfurt Am Worthersee
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00144 Roma
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