Energy-Efficient Dynamic Workflow Scheduling in Cloud Environments Using Deep Learning

Energy-Efficient Dynamic Workflow Scheduling in Cloud Environments Using Deep Learning

Dynamic workflow scheduling in cloud environments is a challenging task due to task dependencies, fluctuating workloads, resource variability, and the need to balance makespan and energy consumption. This study presents a novel scheduling framework that integrates Graph Neural Networks (GNNs) with D...

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Bibliographic Details
Main Authors: Sunera Chandrasiri, Dulani Meedeniya
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Sensors
Subjects:
artificial intelligence
cloud workflow scheduling
Graph Neural Network
multi-objective optimization
reinforcement learning
Online Access:https://www.mdpi.com/1424-8220/25/5/1428

Internet

https://www.mdpi.com/1424-8220/25/5/1428

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