Blar i SINTEF Open på forfatter "Prodan, Radu"

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    • 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 (Peer reviewed; Journal article, 2021)
      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 ...

    • Big Data Pipelines on the Computing Continuum: Tapping the Dark Data 

      Roman, Dumitru; Prodan, Radu; Nikolov, Nikolay; Soylu, Ahmet; Matskin, Mihhail; Marrella, Andrea; Kimovski, Dragi; Elvesæter, Brian; Simonet-Boulogne, Anthony; Ledakis, Giannis; Song, Hui; Leotta, Francesco; Kharlamov, Evgeny (Peer reviewed; Journal article, 2022)
      The computing continuum enables new opportunities for managing big data pipelines concerning efficient management of heterogeneous and untrustworthy resources. We discuss the big data pipelines lifecycle on the computing ...

    • 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 (Chapter, 2021)

    • Smart Data Placement for Big Data Pipelines: An Approach based on the Storage-as-a-Service Model 

      Khan, Akif Quddus; Nikolov, Nikolay Vladimirov; Matskin, Mihhail; Prodan, Radu; Song, Hui; Roman, Dumitru; Soylu, Ahmet (Chapter, 2022)
      The development of big data pipelines is a challenging task, especially when data storage is considered as part of the data pipelines. Local storage is expensive, hard to maintain, comes with several challenges (e.g., data ...

    • Smart Data Placement Using Storage-as-a-Service Model for Big Data Pipelines 

      Khan, Akif Quddus; Nikolov, Nikolay; Matskin, Minhail; Prodan, Radu; Roman, Dumitru; Sahin, Bekir; Bussler, Christoph; Soylu, Ahmet (Peer reviewed; Journal article, 2023)
      Big data pipelines are developed to process data characterized by one or more of the three big data features, commonly known as the three Vs (volume, velocity, and variety), through a series of steps (e.g., extract, ...