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Publication . Preprint . Article . 2017 . Embargo end date: 01 Jan 2017

INDIGO-DataCloud:A data and computing platform to facilitate seamless access to e-infrastructures

Collaboration, INDIGO-DataCloud; Salomoni, Davide; Campos, Isabel; Gaido, Luciano; de Lucas, Jesus Marco; Solagna, Peter; Gomes, Jorge; +57 Authors
Open Access
Published: 06 Nov 2017
Publisher: arXiv
This paper describes the achievements of the H2020 project INDIGO-DataCloud. The project has provided e-infrastructures with tools, applications and cloud framework enhancements to manage the demanding requirements of scientific communities, either locally or through enhanced interfaces. The middleware developed allows to federate hybrid resources, to easily write, port and run scientific applications to the cloud. In particular, we have extended existing PaaS (Platform as a Service) solutions, allowing public and private e-infrastructures, including those provided by EGI, EUDAT, and Helix Nebula, to integrate their existing services and make them available through AAI services compliant with GEANT interfederation policies, thus guaranteeing transparency and trust in the provisioning of such services. Our middleware facilitates the execution of applications using containers on Cloud and Grid based infrastructures, as well as on HPC clusters. Our developments are freely downloadable as open source components, and are already being integrated into many scientific applications.
Comment: 39 pages, 15 figures.Version accepted in Journal of Grid Computing

Distributed, Parallel, and Cluster Computing (cs.DC), FOS: Computer and information sciences, Computer Science - Distributed, Parallel, and Cluster Computing

[14] S. Bagnasco, S. Vallero and V. Zaccolo CHEP 2016, Journal of Physics: Conference Series, Volume 898 (2017) [16] PRISMA: [17] Opencityplatform: [18] See [19] See [20] A Ceccanti, M Hardt, B Wegh, AP Millar, M Caberletti, E Vianello and S Licehammer J. Phys.: Conf. Ser. 898 02016

[21] See

Funded by
EC| INDIGO-DataCloud
INtegrating Distributed data Infrastructures for Global ExplOitation
  • Funder: European Commission (EC)
  • Project Code: 653549
  • Funding stream: H2020 | RIA
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