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The Journal of Supercomputing

Erschienen in:

13.04.2017

Cloud workflow scheduling with hybrid resource provisioning

verfasst von: Long Chen, Xiaoping Li

Erschienen in: The Journal of Supercomputing | Ausgabe 12/2018

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Abstract

Resource provisioning strategies are crucial for workflow scheduling problems which are widespread in cloud computing. The main challenge lies in determining the amounts of reserved and on-demand resources to meet users’ requirements. In this paper, we consider the cloud workflow scheduling problem with hybrid resource provisioning to minimize the total renting cost, which is NP-hard and has not been studied yet. An iterative population-based meta-heuristic is developed. According to the shift vectors obtained during the search procedure, timetables are computed quickly. The appropriate amounts of reserved and on-demand resources are determined by an incremental optimization method. The utilization of each resource is balanced in a swaying way, in terms of which the probabilistic matrix is updated for the next iteration. The proposed algorithm is compared with modified existing algorithms for similar problems. Experimental results demonstrate effectiveness and efficiency of the proposed algorithm.

Vorheriger Artikel A design and implementation of a framework for games in IoT

Nächster Artikel Host load prediction with long short-term memory in cloud computing

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Titel: Cloud workflow scheduling with hybrid resource provisioning
verfasst von: Long Chen
Xiaoping Li
Publikationsdatum: 13.04.2017
Verlag: Springer US
Erschienen in: The Journal of Supercomputing / Ausgabe 12/2018
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-017-2043-5

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