dc.contributor.author | Roman, Dumitru | |
dc.contributor.author | Nikolov, Nikolay | |
dc.contributor.author | Soylu, Ahmet | |
dc.contributor.author | Elvesæter, Brian | |
dc.contributor.author | Song, Hui | |
dc.contributor.author | Prodan, Radu | |
dc.contributor.author | Kimovski, Dragi | |
dc.contributor.author | Marrella, Andrea | |
dc.contributor.author | Leotta, Francesco | |
dc.contributor.author | Matskin, Mihhail | |
dc.contributor.author | Ledakis, Giannis | |
dc.contributor.author | Theodosiou, Konstantinos | |
dc.contributor.author | Simonet-Boulogne, Anthony | |
dc.contributor.author | Perales, Fernando | |
dc.contributor.author | Kharlamov, Evgeny | |
dc.contributor.author | Ulisses, Alexandre | |
dc.contributor.author | Solberg, Arnor | |
dc.contributor.author | Ceccarelli, Raffaele | |
dc.date.accessioned | 2022-03-21T08:29:16Z | |
dc.date.available | 2022-03-21T08:29:16Z | |
dc.date.created | 2022-01-13T20:55:40Z | |
dc.date.issued | 2021-12-15 | |
dc.identifier.isbn | 978-1-6654-2744-9 | |
dc.identifier.isbn | 978-1-6654-2745-6 | |
dc.identifier.issn | 1530-1346 | |
dc.identifier.issn | 2642-7389 | |
dc.identifier.uri | https://hdl.handle.net/11250/2986343 | |
dc.description.abstract | Organisations possess and continuously generate huge amounts of static and stream data, especially with the proliferation of Internet of Things technologies. Collected but unused data, i.e., Dark Data, mean loss in value creation potential. In this respect, the concept of Computing Continuum extends the traditional more centralised Cloud Computing paradigm with Fog and Edge Computing in order to ensure low latency pre-processing and filtering close to the data sources. However, there are still major challenges to be addressed, in particular related to management of various phases of Big Data processing on the Computing Continuum. In this paper, we set forth an ecosystem for Big Data pipelines in the Computing Continuum and introduce five relevant real-life example use cases in the context of the proposed ecosystem. | en_US |
dc.description.sponsorship | This work was partly funded by the European Commission Horizon 2020 project “DataCloud: Enabling The Big Data Pipeline Lifecycle on the Computing Continuum” (Grant number 101016835). | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers | en_US |
dc.relation.ispartofseries | Proceedings of the IEEE Symposium on Computers and Communications;2021 IEEE Symposium on Computers and Communications (ISCC) | |
dc.subject | Big data | en_US |
dc.subject | Computing continuums | en_US |
dc.subject | Dark data | en_US |
dc.subject | Data pipelines | en_US |
dc.subject | Cloud-fog-edge computing | en_US |
dc.title | Big Data Pipelines on the Computing Continuum: Ecosystem and Use Cases Overview | en_US |
dc.type | Peer reviewed | en_US |
dc.type | Journal article | en_US |
dc.description.version | acceptedVersion | en_US |
cristin.ispublished | true | |
cristin.fulltext | postprint | |
cristin.qualitycode | 1 | |
dc.identifier.doi | https://doi.org/10.1109/ISCC53001.2021.9631410 | |
dc.identifier.cristin | 1980819 | |
dc.source.journal | Proceedings of the IEEE Symposium on Computers and Communications | en_US |
dc.source.volume | 26 | en_US |
dc.source.issue | 26 | en_US |
dc.source.pagenumber | 4 | en_US |
dc.relation.project | Horisont 2020: EC/H2020/101016835 | en_US |