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Budget-aware Static Scheduling of Stochastic Workflows with DIET

Yves Caniou 1, 2 Eddy Caron 1, 2 Aurélie Kong Win Chang 1, 3, 2 Yves Robert 3, 2, 4 
Abstract : Previous work has introduced a Cloud platform model and budget-aware static algorithms to schedule stochastic workflows on such platforms. In this paper, we compare the performance of these algorithms obtained via simulation and via execution on an actual platform, Grid'5000. We focus on DIET, a widely used workflow engine, and detail the extensions that were implemented to conduct the comparison. We also detail additional code that we made available in order to automate and to ease the reproducibility of such experiments.
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Submitted on : Thursday, September 2, 2021 - 10:46:12 PM
Last modification on : Friday, September 30, 2022 - 4:12:26 AM
Long-term archiving on: : Friday, December 3, 2021 - 9:09:40 PM


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  • HAL Id : hal-03332601, version 1



Yves Caniou, Eddy Caron, Aurélie Kong Win Chang, Yves Robert. Budget-aware Static Scheduling of Stochastic Workflows with DIET. ADVCOMP 2021 - 15th International Conference on Advanced Engineering Computing and Applications in Sciences, Oct 2021, Barcelona, Spain. pp.1-8. ⟨hal-03332601⟩



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