Search Results - Review of resource-aware parallel and distributed computing

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  1. 1

    Optimization of resource-aware parallel and distributed computing: a review by Czarnul, Paweł, Antal, Marcel, Baniata, Hamza, Griebler, Dalvan, Kertesz, Attila, Kessler, Christoph W., Kouloumpris, Andreas, Kovačić, Salko, Markus, Andras, Michael, Maria K., Nikolaou, Panagiota, Öz, Isil, Prodan, Radu, Rakić, Gordana

    ISSN: 1573-0484, 0920-8542, 1573-0484
    Published: New York Springer Nature B.V 09.05.2025
    Published in The Journal of supercomputing (09.05.2025)
    “…This paper presents a review of state-of-the-art solutions concerning the optimization of computing in the field of parallel and distributed systems…”
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    Journal Article
  2. 2

    Optimization of resource-aware parallel and distributed computing: a review: Optimization of resource-aware parallel by Czarnul, Paweł, Antal, Marcel, Baniata, Hamza, Griebler, Dalvan, Kertesz, Attila, Kessler, Christoph W., Kouloumpris, Andreas, Kovačić, Salko, Markus, Andras, Michael, Maria K., Nikolaou, Panagiota, Öz, Isil, Prodan, Radu, Rakić, Gordana

    ISSN: 1573-0484
    Published: New York Springer US 09.05.2025
    Published in The Journal of supercomputing (09.05.2025)
    “…This paper presents a review of state-of-the-art solutions concerning the optimization of computing in the field of parallel and distributed systems…”
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    Journal Article
  3. 3

    MF-Storm: a maximum flow-based job scheduler for stream processing engines on computational clusters to increase throughput by Muhammad, Asif, Abdul Qadir, Muhammad

    ISSN: 2376-5992, 2376-5992
    Published: San Diego PeerJ. Ltd 26.09.2022
    Published in PeerJ. Computer science (26.09.2022)
    “…A scheduling algorithm tries to schedule multiple computational tasks on a cluster of multiple computing nodes to maximize throughput with optimal utilization of computational and communicational resources…”
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    Journal Article
  4. 4

    Advancements in heuristic task scheduling for IoT applications in fog-cloud computing: challenges and prospects by Alsadie, Deafallah

    ISSN: 2376-5992, 2376-5992
    Published: United States PeerJ. Ltd 17.06.2024
    Published in PeerJ. Computer science (17.06.2024)
    “… This article presents a comprehensive review of the advancements in task scheduling methodologies for fog computing systems, covering priority-based, greedy heuristics, metaheuristics, learning-based…”
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    Journal Article