| [1] | Dumitru Roman, Nikolay Nikolov, Ahmet Soylu, Brian Elvesaeter, Hui Song, Radu Prodan, Dragi Kimovski, Andrea Marrella, Francesco Leotta, Mihhail Matskin, Giannis Ledakis, Konstantinos Theodosiou, Anthony Simonet-Boulogne, Fernando Perales, Evgeny Kharlamov, Alexandre Ulisses, Arnor Solberg, Raffaele Ceccarelli, Big Data Pipelines on the Computing Continuum: Ecosystem and Use Cases Overview, In 2021 IEEE Symposium on Computers and Communications (ISCC), IEEE, pp. 1-4, 2021.
[bib][url] [doi] [abstract]
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.
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