Adaptive and Efficient Resource Allocation in Cloud Datacenters Using Actor-Critic Deep Reinforcement Learning

Zheyi Chen; Jia Hu; Geyong Min; Chunbo Luo; Tarek El‐Ghazawi

doi:10.1109/tpds.2021.3132422

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JOURNAL ARTICLE

Adaptive and Efficient Resource Allocation in Cloud Datacenters Using Actor-Critic Deep Reinforcement Learning

Zheyi Chen Jia Hu Geyong Min Chunbo Luo Tarek El‐Ghazawi

Year: 2021 Journal: IEEE Transactions on Parallel and Distributed Systems Vol: 33 (8)Pages: 1911-1923 Publisher: Institute of Electrical and Electronics Engineers

DOI: 10.1109/tpds.2021.3132422

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Abstract

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record

Keywords:

Cloud computing Computer science Reinforcement learning Provisioning Quality of service Resource allocation Scheduling (production processes) Efficient energy use Latency (audio) Distributed computing Energy consumption Resource efficiency Resource management (computing) Computer network Artificial intelligence Mathematical optimization Operating system Engineering Telecommunications

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118

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15.14

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0.99

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Topics

Cloud Computing and Resource Management

Physical Sciences → Computer Science → Information Systems

IoT and Edge/Fog Computing

Physical Sciences → Computer Science → Computer Networks and Communications

Blockchain Technology Applications and Security

Physical Sciences → Computer Science → Information Systems

Adaptive and Efficient Resource Allocation in Cloud Datacenters Using Actor-Critic Deep Reinforcement Learning

Abstract

Metrics

Citation History

Topics

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