Browsing NTNU Open by Author "Khan, Akif Quddus"

Now showing items 1-9 of 9

    • 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 ...

    • 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 for Big Data Pipelines with Storage-as-a-Service Integration 

      Khan, Akif Quddus (Master thesis, 2022)
      Big data pipelines are developed to process big data and turn it into useful information. They are designed to support one or more of the three big data features commonly known as the three Vs (Volume, Velocity, and Variety). ...

    • 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 (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, ...

    • A Taxonomy for Cloud Storage Cost 

      Khan, Akif Quddus; Nikolov, Nikolay Vladimirov; Matskin, Mihhail; Prodan, Radu; Bussler, Christoph; Roman, Dumitru; Soylu, Ahmet (Peer reviewed; Journal article, 2023)
      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 (Peer reviewed; 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 ...

    • Towards Graph-based Cloud Cost Modelling and Optimisation 

      Khan, Akif Quddus; Nikolov, Nikolay Vladimirov; Matskin, Mihhail; Prodan, Radu; Bussler, Christoph; Roman, Dumitru; Soylu, Ahmet (Chapter, 2023)
      Cloud computing has become an increasingly popular choice for businesses and individuals due to its flexibility, scalability, and convenience; however, the rising cost of cloud resources has become a significant concern ...