2023-2025. Horizon Europe Programme. Grant number 101092644.
The goal of NEARDATA is to create an extreme data infrastructure mediating data flows between Object Storage and Data Analytics platforms across the Compute Continuum. Our novel XtremeDataHub platform is an intermediary data service that intercepts and optimises data flows (S3 API, stream APIs) with high performance near-data connectors (Cloud/Edge). Finally, our unique Data Broker service will provide secure data access and orchestration of dispersed data sources thanks to TEEs and federated learning architectures. Our NEARDATA platform is a novel technology for data mining of large and dispersed unstructured data sets that can be deployed in the Cloud and in the Edge (HPC, IoT Devices), that leverages advanced AI technologies and offers a novel confidential cybersecurity layer for trusted data computation.
2023-2025. Horizon Europe Programme. Grant number 101092646.
CloudSkin aims to design a cognitive cloud continuum platform to fully exploit the available Cloud-edge heterogeneous resources, finding the “sweet spot” between the cloud and the edge, and smartly adapting to changes in application behavior via AI. To facilitate automatic deployment, mobility and security of services, CloudSkin will build an innovative universal container-like execution abstraction based on WebAssembly that allows the seamless and trustworthy execution of (legacy) applications across the Cloud-edge continuum.
2023-2025. Horizon Europe Programme. Grant number 101093110.
Data has become one of the most valuable assets driving the digital transformation across a variety of sectors. Current data mining solutions are optimized to deal with specific data requirements but fail to cope as the data characteristics become extreme. There is therefore an urgent need for novel and holistic approaches to enable the development, deployment and efficient execution of data mining workflows across a heterogeneous, secure and energy-efficient compute continuum, while fulfilling the diverse extreme data characteristics.
To fill this technological gap, EXTRACT will deliver …
2023-2025. Funded by the Ministry of Economic Affairs and Digital Transformation and by the European Union-NextGenerationEU, within the framework of the PRTR and the MRR. Programa UNICO I+D Cloud, en el marco del Plan de Recuperación, Transformación y Resiliencia -Financiado por la Unión Europea- Next Generation EU
The objective of the CLOUDLESS project is to develop an edge computing platform for the creation and deployment of open Data Spaces (International Data Spaces). The platform will follow a decentralized distributed architecture that offers event-based open discovery and interconnection services (data brokers) to different data consumers (data consumers) and data providers (data providers). The architecture will also offer secure Cloud/Edge infrastructures that allow efficient data analysis (data connectors) based on variables such as locality, economic cost, privacy or latency. The platform will be validated in different open data spaces such as citizen science, tourism or omics data (genomics and metabolomics).
2020-2023. Funded by the Spanish Ministry of Science, Innovation and Universities, Plan Estatal de Investigación Científica y Técnica y de Innovación. Grant number PID2019-106774RB-C22.
2019-2022. H2020 Research and Innovation. Grant number 825184.
The main goal is to create CloudButton: a Serverless Data Analytics Platform. CloudButton will democratize big data by overly simplifying the overall life cycle and programming model thanks to serverless technologies. To demonstrate the impact of the project, we target two settings with large data volumes: bioinformatics (genomics, metabolomics) and geospatial data (LiDAR, satellital).
2015-2017. H2020 Research and Innovation. Grant number 644182.
The main objective is to create IOStack: a Software-defined Storage toolkit for Big Data on top of the OpenStack platform. IOStack will enable efficient execution of virtualized analytics applications over virtualized storage resources thanks to flexible, automated, and low cost data management models based on software-defined storage (SDS).
2016-2019. Funded by the Spanish Ministry of Economy and Competitiveness (MEYC), Plan Estatal de Investigación Científica y Técnica y de Innovación. Grant number TIN2016-77836-C2-1-R.