A fusion deep Q-learning and particle swarm optimization algorithm for adaptive resource allocation in cloud computing circumstances

Abstract Effective resource allocation in cloud computing continues a critical challenge due to dynamic loads, stringent service-level expectations, and the need to balance execution time, energy, and cost. This study suggests a hybrid framework that integrates Deep Q-Learning (DQL) with Particle Sw...

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Autors principals:	Ahmed Hadi Ali AL-Jumaili, Mohammed E. Seno, Waleed Kareem Awad, Ravie Chandren Muniyandi, Mohammad Kamrul Hasan
Format:	Artigo
Idioma:	Inglês
Publicat:	Nature Portfolio 2026-04-01
Col·lecció:	Scientific Reports
Matèries:	Cloud computing Resource allocation Deep Q-Learning (DQL) Particle swarm optimization (PSO) Hybrid algorithms Reinforcement learning
Accés en línia:	https://doi.org/10.1038/s41598-025-33498-2
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