工业时间敏感网络中任务调度与资源部署联合优化方法及其相关应用

By constructing an industrial time-sensitive network scheduling model and policy network, the coordination problem of cross-cycle equipment deployment and task scheduling was solved, achieving efficient resource utilization and improved production efficiency.

CN122047952BActive Publication Date: 2026-07-17CHANGSHA NENGCHUAN INFORMATION TECH CO LTD +1

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
CHANGSHA NENGCHUAN INFORMATION TECH CO LTD
Filing Date
2026-04-16
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Existing technologies fail to effectively coordinate equipment deployment and task scheduling in industrial time-sensitive networks with multiple continuous production cycles, resulting in resource waste and excessive costs, and failing to meet the dynamic industrial production needs.

Method used

An industrial time-sensitive network scheduling model is constructed. The global embedded state is encoded by a graph neural network, and the system is combined with a policy network to make decisions on equipment deployment and task scheduling. The policy is updated through a reward mechanism to achieve cross-cycle optimization.

Benefits of technology

Dynamically coordinate equipment reuse and task scheduling to improve task completion rate and network resource utilization efficiency, reduce costs, and enhance production efficiency and resource utilization.

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Abstract

本发明公开了一种工业时间敏感网络中任务调度与资源部署联合优化方法及其相关应用。该方法包括:构建含多个工业生产周期的工业时间敏感网络调度模型与智能体交互环境,智能体配置为在每一个生产周期通过图神经网络编码得到全局嵌入状态,经策略网络依次执行设备部署与任务调度决策,周期结束后计算奖励值更新策略网络,迭代完成全周期联合优化,从而在保证所有关键通信流按期送达的同时,实现跨周期地优化设备部署和任务调度,实现在每个生产周期开始时科学决策,从而克服传统单周期调度的局限,在更长的时间跨度上提升工业生产的整体效率和网络资源利用率,有效提升生产效率,并降低成本。
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