Predictive State-Aware Deep Reinforcement Learning With Hyper-Heuristic for Resolving Conflicting Objectives in Scientific Workflow Scheduling

Scientific workflows in cloud environments are highly complex and dynamic, necessitating intelligent and flexible scheduling solutions to handle important factors, including resource heterogeneity, budget constraints, deadlines, and ever-changing workload requirements. In contrast to traditional sch...

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Bibliographic Details

Published in:	IEEE Access
Main Authors:	Awadh Salem Bajaher, Nor Asilah Wati Abdul Hamid, Idawaty Ahmad, Zurina Mohd Hanapi
Format:	Article
Language:	English
Published:	IEEE 2025-01-01
Subjects:	Cloud computing scientific workflow tasks workflow scheduling deadline budget hyper-heuristic generation
Online Access:	https://ieeexplore.ieee.org/document/11186249/