A Deep Reinforcement Learning Approach to the Optimization of Data Center Task Scheduling

A Deep Reinforcement Learning Approach to the Optimization of Data Center Task Scheduling

With more businesses are running online, the scale of data centers is increasing dramatically. The task-scheduling operation with traditional heuristic algorithms is facing the challenges of uncertainty and complexity of the data center environment. It is urgent to use new technology to optimize the...

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Bibliographic Details
Main Authors:	Haiying Che, Zixing Bai, Rong Zuo, Honglei Li
Format:	Article
Language:	English
Published:	Wiley 2020-01-01
Series:	Complexity
Online Access:	http://dx.doi.org/10.1155/2020/3046769
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