Prediction-based Coflow Scheduling - LAAS - Laboratoire d'Analyse et d'Architecture des Systèmes
Pré-Publication, Document De Travail (Preprint/Prepublication) Année : 2023

Prediction-based Coflow Scheduling

Ordonnancement de coflows à partir de prédictions

Oumayma Haddaji
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  • PersonId : 1291126

Résumé

We explore the problem of minimizing the weighted average coflow completion time of coflows when flow sizes are unknown but unreliable predictions on them are available. We propose to use Sincronia, a 4-approximation algorithm when actual flow sizes are known, directly on the predictions. For this variant of Sincronia, we obtain a finite upper bound on the approximation ratio that combines unreliability on predictions and the weights of the coflows. On several numerical experiments, it is shown that this bound is too conservative, and that in practice Sincronia with predictions has a much better performance on average as well as in the worst-case.
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Dates et versions

hal-04231370 , version 1 (06-10-2023)

Licence

Domaine public

Identifiants

  • HAL Id : hal-04231370 , version 1

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Olivier Brun, Balakrishna Prabhu, Oumayma Haddaji. Prediction-based Coflow Scheduling. 2023. ⟨hal-04231370⟩
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