强化学习
计算机科学
分布式计算
云计算
调度(生产过程)
服务质量
工作流程
人工智能
实时计算
计算机网络
数学优化
操作系统
数据库
数学
作者
Judy C. Guevara,Ricardo da Silva Torres,Luiz F. Bittencourt,Nelson L. S. da Fonseca
标识
DOI:10.1109/globecom48099.2022.10001644
摘要
In this paper, we propose three multi-objective task scheduling algorithms for the cloud-fog continuum, that minimize both the makes pan and processing cost of workflows, considering the QoS requirements of the applications. Numerical results show that the scheduler based on Reinforcement Learning outperforms those based on classical optimization.
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