EETS: An energy-efficient task scheduler in cloud computing based on improved DQN algorithm

The huge energy consumption of data centers in cloud computing leads to increased operating costs and high carbon emissions to the environment. Deep Reinforcement Learning (DRL) technology combines of deep learning and reinforcement learning, which has an obvious advantage in solving complex task sc...

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Главные авторы:	Huanhuan Hou, Azlan Ismail
Формат:	Artigo
Язык:	Inglês
Опубликовано:	Springer 2024-10-01
Серии:	Journal of King Saud University: Computer and Information Sciences
Предметы:	Cloud computing Task scheduling Deep reinforcement learning Energy-efficient Double dueling DQN Prioritized experience replay
Online-ссылка:	http://www.sciencedirect.com/science/article/pii/S1319157824002660
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