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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Hlavní autoři:	Huanhuan Hou, Azlan Ismail
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Springer 2024-10-01
Edice:	Journal of King Saud University: Computer and Information Sciences
Témata:	Cloud computing Task scheduling Deep reinforcement learning Energy-efficient Double dueling DQN Prioritized experience replay
On-line přístup:	http://www.sciencedirect.com/science/article/pii/S1319157824002660
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