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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Үндсэн зохиолчид:	Awadh Salem Bajaher, Nor Asilah Wati Abdul Hamid, Idawaty Ahmad, Zurina Mohd Hanapi
Формат:	Artigo
Хэл сонгох:	Inglês
Хэвлэсэн:	IEEE 2025-01-01
Цуврал:	IEEE Access
Нөхцлүүд:	Cloud computing scientific workflow tasks workflow scheduling deadline budget hyper-heuristic generation
Онлайн хандалт:	https://ieeexplore.ieee.org/document/11186249/
Шошгууд:	Шошго нэмэх Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!