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Smart Manufacturing Scheduling System: DQN based on Cooperative Edge Computing

机译:智能制造调度系统:基于协同边缘计算的DQN

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In this paper, Deep Q-Network (DQN) was adopted to solve the Job shop Scheduling Problem (JSP) in the smart factory process. On the other hand, cloud computing has sensitive issues in the manufacturing process such as communication delay time and security problems. Research on various aspects of introducing an edge computing system to replace it has been conducted. We propose cooperative scheduling among edge devices in a Multi access Edge Computing (MEC) structure for scheduling without the help of a cloud center in a smart factory edge computing environment. Moreover, efficient DQN is used for experiments based on transfer learning data, and the proposed framework is compared and analyzed with existing frameworks from the perspective of provider a smart factory service.
机译:在本文中,采用深Q网络(DQN)解决了智能工厂过程中的作业商店调度问题(JSP)。另一方面,云计算在制造过程中具有敏感的问题,例如通信延迟时间和安全问题。引入边缘计算系统的各个方面的研究已经进行了。我们在多访问边缘计算(MEC)结构中的边缘设备中提出了合作调度,以便在智能工厂边缘计算环境中没有云中心的帮助。此外,高效的DQN用于基于转移学习数据的实验,并将所提出的框架与来自提供商的智能工厂服务的角度进行比较和分析现有框架。

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