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The Journal of Supercomputing

Erschienen in:

25.09.2019

Combinatorial meta-heuristics approaches for DVFS-enabled green clouds

verfasst von: Lourdes Mary Amulu, Ravi Ramraj

Erschienen in: The Journal of Supercomputing | Ausgabe 8/2020

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Abstract

Many scientific applications used in decision support systems successfully make use of nature-based resourceful techniques. The advancements being made in successfully mimicking nature are laying the path for designing energy-efficient clouds. Two meta-heuristic techniques including ant colony optimization and particle swarm optimization, in combination with Bayesian and fuzzy approach, are proposed to be used in this research for designing an energy-efficient cloud system, which adopts the dynamic voltage and frequency scaling (DVFS) method. As DVFS is increasingly becoming an industry standard owing to its incorporation into the CPU hardware, appropriate software-oriented approaches are essential to calibrate the current methodologies. Our research aims at minimizing the accomplishment time and cost, enhancing user satisfaction, and lowering energy consumption. We generated results that excelled the current performance factors on multiple counts.

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Titel: Combinatorial meta-heuristics approaches for DVFS-enabled green clouds
verfasst von: Lourdes Mary Amulu
Ravi Ramraj
Publikationsdatum: 25.09.2019
Verlag: Springer US
Erschienen in: The Journal of Supercomputing / Ausgabe 8/2020
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-019-02997-1

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