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Updated: Jan 12, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

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可扩展的混合框架,用于实时和非实时任务调度在雾计算使用联合强化学习和PSO GA

Fei Liu1, ZhiLi Liu2, XiaoHong Liu3

  • 1School of Computer Science and Engineering, Hunan University of Information Technology, Changsha Hunan, 410151, China.

Scientific reports
|November 3, 2025
PubMed
概括

FRAHTOS优化了物联网 (IoT) 任务调度,使用联合增强学习和混合优化. 该框架显著提高了任务完成率,并减少了分散边缘计算应用程序的延迟时间.

关键词:
分布式集群 分布式集群 分布式集群货运公司FRAHTOS在FRL中,FRL是FRL.雾计算的计算方法延迟时间 延迟时间 延迟时间负载预测的预测.在MDP中,MDP是指MDP中的一个.公共服务部门-GAGA可扩展性 可扩展性任务安排 任务安排这就是VAE的意义.

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