QHRMOF: A Quantum-Inspired hybrid Multi-Objective framework for Energy-Efficient task scheduling and load balancing in cloud computing

Abstract The swift expansion of cloud computing services has resulted in a notable increase in energy consumption, presenting challenges for sustainability and effective resource management in cloud data centres. This paper introduces a novel Quantum-Inspired Hybrid Reinforcement Learning and Multi-...

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Hlavní autoři:	Umesh Kumar Lilhore, Scaria Alex, Vince Paul, Rahoof Puthan Purayil, Sultan Mesfer A Aldossary, Sarita Simaiya, Ehab seif Ghith, Heba G. Mohamed, Monish Khan
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	SpringerOpen 2025-10-01
Edice:	Journal of Cloud Computing: Advances, Systems and Applications
Témata:	Cloud computing Quantum-Inspired evolutionary algorithm Deep reinforcement learning Multi-Objective optimization Task scheduling Load balancing
On-line přístup:	https://doi.org/10.1186/s13677-025-00777-2
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