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The Journal of Supercomputing

Erschienen in:

01.07.2015

Dynamically hierarchical resource-allocation algorithm in cloud computing environment

verfasst von: Zhanjie Wang, Xianxian Su

Erschienen in: The Journal of Supercomputing | Ausgabe 7/2015

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Abstract

The development of big data challenges the computing power and communication capability of cloud architecture, but traditional resource-allocation algorithms perform poorly due to the large-scale communication among cloud nodes. In this paper, a dynamically hierarchical, resource-allocation algorithm is proposed for multiple cloud nodes collaborating in big data environment. Using fuzzy pattern recognition, the algorithm dynamically divides tasks and nodes into different levels based on computing power and storage factors. Thus a dynamically adjusted mapping is generated between tasks and nodes. When a new task arrives, only the nodes corresponding to the task level join in the bid. The algorithm takes advantages of dynamical hierarchy to reduce the communication traffic during resource allocation. Both theoretical and experimental results illustrate that the proposed algorithm outperforms the MinMin algorithm in terms of communication traffic and makespan.

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Titel: Dynamically hierarchical resource-allocation algorithm in cloud computing environment
verfasst von: Zhanjie Wang
Xianxian Su
Publikationsdatum: 01.07.2015
Verlag: Springer US
Erschienen in: The Journal of Supercomputing / Ausgabe 7/2015
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-015-1416-x

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