Suchergebnisse - Review of resource-aware parallel and distributed computing

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  1. 1

    Optimization of resource-aware parallel and distributed computing: a review von 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
    Veröffentlicht: New York Springer Nature B.V 09.05.2025
    Veröffentlicht 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 von 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
    Veröffentlicht: New York Springer US 09.05.2025
    Veröffentlicht 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 …”
    Volltext
    Journal Article
  3. 3

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

    ISSN: 2376-5992, 2376-5992
    Veröffentlicht: San Diego PeerJ. Ltd 26.09.2022
    Veröffentlicht 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 von Alsadie, Deafallah

    ISSN: 2376-5992, 2376-5992
    Veröffentlicht: United States PeerJ. Ltd 17.06.2024
    Veröffentlicht 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