A Data-Aware Scheduling Strategy for Executing Large-Scale Distributed Workflows

A Data-Aware Scheduling Strategy for Executing Large-Scale Distributed Workflows

Task scheduling is a crucial key component for the efficient execution of data-intensive applications on distributed environments, by which many machines must be coordinated to reduce execution times and bandwidth consumption. This paper presents ADAGE, a data-aware scheduler designed to efficiently...

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Bibliographic Details
Main Authors: Salvatore Giampa, Loris Belcastro, Fabrizio Marozzo, Domenico Talia, Paolo Trunfio
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Data-aware scheduler
workflow scheduling
distributed workflows
parallel programming
distributed computing
exascale computing
Online Access:https://ieeexplore.ieee.org/document/9382295/

Internet

https://ieeexplore.ieee.org/document/9382295/

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