Openfund

CORDIS · ENACT

Adaptive Scheduling and Deployments of Data Intensive Workloads on Energy Efficient Edge to Cloud Continuum

Код
ENACT
Програма
HORIZON
Процедура
HORIZON-CL4-2023-DATA-01-04
Статус
SIGNED
Период
01.01.2024 – 31.12.2026
Принос на ЕС (целият консорциум)5 055 074 €
Принос на ЕС за българските участници278 750 €

Официални данни · CORDIS · синхронизирано 17.10.2026 10:16 · официален запис

Участници

ОрганизацииРоляДържаваБезвъзмездна помощ
ETHNIKO KENTRO EREVNAS KAI TECHNOLOGIKIS ANAPTYXISкоординаторEL751 875 €
INFORMATION CATALYST SLучастникES591 250 €
UNIVERSITAT POLITECNICA DE VALENCIAучастникES382 969 €
SIEMENS SRLучастникRO336 000 €
FUJITSU TECHNOLOGY SOLUTIONS SPZOOучастникPL315 000 €
ASOCIACION DE EMPRESAS TECNOLOGICAS INNOVALIAучастникES313 125 €
FOUR DOT INFINITY INFORMATION AND TELECOMMUNICATIONS SOLUTIONS PRIVATE COMPANYучастникEL299 375 €
DIGITAL SYSTEMS 4.0участникBG278 750 €
UNPARALLEL INNOVATION LDAучастникPT276 250 €
ARCTUR RACUNALNISKI INZENIRING DOOучастникSI248 750 €
EREVNITIKO PANEPISTIMIAKO INSTITOUTO SYSTIMATON EPIKOINONION KAI YPOLOGISTONучастникEL230 625 €
DUNAVNET LIMITEDучастникIE227 493 €
EVS BROADCAST EQUIPMENT - PORTUGAL LDAучастникPT223 750 €
PANEPISTIMIO DYTIKIS MAKEDONIASучастникEL221 875 €
ECLIPSE FOUNDATION EUROPE GMBHучастникDE181 450 €
EITB MEDIA SAучастникES100 762 €
OSOIGO S.L.участникES75 775 €
SOCIEDAD DE PROYECTOS PARA LA TRANSFORMACION DIGITAL SAучастникES0 €

Описание

ENACT develops cutting-edge techniques and technology solutions to realise a Cognitive Computing Continuum (CCC) that can address the needs for optimal (edge and Cloud) resource management and dynamic scaling, elasticity, and portability of hyper-distributed data-intensive applications. At infrastructure level, the project brings visibility to distributed edge and Cloud resources by developing Dynamic Graph Models capable of capturing and visualising the real-time and historic status information, connectivity types, dependencies, energy consumption etc. from diverse edge and Cloud resources. The graph models are used by AI (Graph Neural Networks - GNN) models and Deep Reinforcement Learning (DRL) agents to suggest the optimal deployment configurations for hyper distributed applications considering their specific needs. The AI (GNN and DRL) models are packaged as an intelligent decision-making engine that can replace the scheduling component of open-source solutions such as KubeEdge. This will enable real-time and predictive management of distributed infrastructure and applications. To take full advantage of the potential (compute, storage, energy efficiency etc) opportunities in the CCC, ENACT will develop an innovative Application Programming Model (APM). The APM will support the development of distributed platform agnostic applications, capable of self-determining their optimal deployment and optimal execution configurations while taking advantage of diverse resources in the CCC. An SDK to develop APM-based distributed applications will be developed. Moreover, services for automatic (zero-touch provisioning-based) resource configuration and (telemetry) data collections are developed to help design and update dynamic graph models. ENACT CCC solutions will be validated in 3 use-cases with challenging resource and application requirements. International collaboration is planned as Japan Productivity Center has committed to support with knowledge sharing.

Официални данни · CORDIS · синхронизирано 17.10.2026 10:16 · официален запис · Лиценз: © European Union, CC BY 4.0 (Commission reuse policy).