Blar i NTNU Open på forfatter "Nikolov, Nikolay"

Viser treff 1-5 av 5

    • Big data workflows: Locality-aware orchestration using software containers 

      Corodescu, Andrei-Alin; Nikolov, Nikolay; Khan, Akif Quddus; Soylu, Ahmet; Matskin, Mihhail; Payberah, Amir H.; Roman, Dumitru (Journal article; Peer reviewed, 2021)
      The emergence of the Edge computing paradigm has shifted data processing from centralised infrastructures to heterogeneous and geographically distributed infrastructures. Therefore, data processing solutions must consider ...

    • Conceptualization and scalable execution of big data workflows using domain-specific languages and software containers 

      Nikolov, Nikolay; Dessalk, Yared Dejene; Khan, Akif Quddus; Soylu, Ahmet; Matskin, Mihhail; Payberah, Amir; Roman, Dumitru (Journal article; Peer reviewed, 2021)
      Big Data processing, especially with the increasing proliferation of Internet of Things (IoT) technologies and convergence of IoT, edge and cloud computing technologies, involves handling massive and complex data sets on ...

    • The Data Value Quest: A Holistic Semantic Approach at Bosch 

      Zhou, Baifan; Zheng, Zhuoxun; Zhou, Dongzhuoran; Cheng, Gong; Jimenez-Ruiz, Ernesto; Trung-Kien, Tran; Stepanova, Daria; Gad-Elrab, Mohamed H.; Nikolov, Nikolay; Soylu, Ahmet; Kharlamov, Evgeny (Journal article; Peer reviewed, 2022)
      Modern industry witnesses a fast growth in volume and complexity of heterogeneous manufacturing (big) data [1, 2] thanks to the technological advances of Industry 4.0 [1, 3], including development in perception, communication, ...

    • Locality-Aware Workflow Orchestration for Big Data 

      Corodescu, Andrei-Alin; Nikolov, Nikolay; Khan, Akif Quddus; Soylu, Ahmet; Matskin, Mihhail; Payberah, Amir; Roman, Dumitru (Chapter, 2021)
      The development of the Edge computing paradigm shifts data processing from centralised infrastructures to heterogeneous and geographically distributed infrastructure. Such a paradigm requires data processing solutions that ...

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