Data-Aware Approximate Workflow Scheduling

Optimization of data placement in complex scientific workflows has become very crucial since the large amounts of data generated by these workflows significantly increases the turnaround time of the end-to-end application. It is almost impossible to make an optimal scheduling for the end-to-end work...

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Veröffentlicht in:	arXiv.org 2018-05
Hauptverfasser:	Yin, Dengpan, Kosar, Tevfik
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Complexity Crossovers Mutation Optimization Production scheduling Scheduling Workflow
Online-Zugang:	Volltext
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