• Big Data Pipelines on the Computing Continuum: Ecosystem and Use Cases Overview 

      Roman, Dumitru; Nikolov, Nikolay; Soylu, Ahmet; Elvesæter, Brian; Song, Hui; Prodan, Radu; Kimovski, Dragi; Marrella, Andrea; Leotta, Francesco; Matskin, Mihhail; Ledakis, Giannis; Theodosiou, Konstantinos; Simonet-Boulogne, Anthony; Perales, Fernando; Kharlamov, Evgeny; Ulisses, Alexandre; Solberg, Arnor; Ceccarelli, Raffaele (Proceedings of the IEEE Symposium on Computers and Communications;2021 IEEE Symposium on Computers and Communications (ISCC), Peer reviewed; Journal article, 2021-12-15)
      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 ...
    • DataCloud: Enabling the Big Data Pipelines on the Computing Continuum 

      Roman, Dumitru; Nikolov, Nikolay; Elvesæter, Brian; Soylu, Ahmet; Prodan, Radu; Kimovski, Dragi; Marrella, Andrea; Leotta, Francesco; Benvenuti, Dario; Matskin, Mihhail; Ledakis, Giannis; Simonet-Boulogne, Anthony; Perales, Fernando; Kharlamov, Evgeny; Ulisses, Alexandre; Solberg, Arnor; Ceccarelli, Raffaele (Lecture Notes in Business Information Processing;Volume 415, Conference object, 2021-05)
      With the recent developments of Internet of Things (IoT) and cloud-based technologies, massive amounts of data are generated by heterogeneous sources and stored through dedicated cloud solutions. Often organizations generate ...