• 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 ...
    • 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 (Computer;Volume: 55, Issue: 11, Peer reviewed; Journal article, 2022-10-25)
      Big Data pipelines are essential for leveraging Dark Data, i.e., data collected but not used and turned into value. However, tapping their potential requires going beyond existing approaches and frameworks for Big Data ...
    • Container-Based Data Pipelines on the Computing Continuum for Remote Patient Monitoring 

      Nikolov, Nikolay Vladimirov; Solberg, Arnor; Prodan, Radu; Soylu, Ahmet; Matskin, Mihhail; Roman, Dumitru (Computer;, Peer reviewed; Journal article, 2023)
      Diagnosing, treatment, and follow-up care of patients is happening increasingly through telemedicine, especially in remote areas where direct interaction is hindered. Over the past three years, following the COVID-19 ...
    • 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 ...
    • 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)
    • A Taxonomy for Cloud Storage Cost 

      Khan, Akif Quddus; Nikolov, Nikolay Vladimirov; Matskin, Mihhail; Prodan, Radu; Bussler, Christoph; Roman, Dumitru; Soylu, Ahmet (Communications in Computer and Information Science (CCIS);, Chapter; Peer reviewed; Conference object; Journal article, 2024)
      The cost of using cloud storage services is complex and often an unclear structure, while it is one of the important factors for organisations adopting cloud storage. Furthermore, organisations take advantage of multi-cloud ...
    • Towards Cloud Storage Tier Optimization with Rule-Based Classification 

      Khan, Akif Quddus; Nikolov, Nikolay Vladimirov; Matskin, Mihhail; Prodan, Radu; Bussler, Christoph; Roman, Dumitru; Soylu, Ahmet (Chapter; Peer reviewed; Conference object; Journal article, 2023)
      Cloud storage adoption has increased over the years as more and more data has been produced with particularly high demand for fast processing and low latency. To meet the users’ demands and to provide a cost-effective ...