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首页> 外文期刊>IEEE transactions on industrial informatics >Dual-Network Task Scheduling inCyber–Physical Systems: A Cooptimization Approach
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Dual-Network Task Scheduling inCyber–Physical Systems: A Cooptimization Approach

机译:双网络任务调度界面 - 物理系统:一种共同化方法

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摘要

The cyber-physical system is highly desirable for real-time perception and dynamic control, especially in task scheduling and network communication for large and complex engineering systems. In most of the applications, the resource scheduling of cyber and physical network are independent on each other, which may cause severe deterioration of the network performance. To implement the cognitive cooperation between the upper layer of industrial services and the underlying network, we propose a cooptimization method in this article. We adopt the software defined networking technology to extract the network control logic, which is integrated with the upper-level task scheduling. This cooptimization scheme can dynamically calculate optimal end-to-end virtual paths over the underlying network infrastructures. Meanwhile, it can also adjust the task scheduling of the upper-level network by signals derived from the underlying network. Simulation results show that our proposed scheme outperforms the traditional method in terms of task acceptance rate, average end-to-end delay, and network load balance degree.
机译:网络物理系统非常希望实时感知和动态控制,尤其是用于大型和复杂工程系统的任务调度和网络通信。在大多数应用中,网络和物理网络的资源调度彼此独立,这可能导致网络性能严重劣化。为了实现工业服务上层与底层网络之间的认知合作,我们提出了本文中的一项高昂化方法。我们采用软件定义的网络技术提取网络控制逻辑,该控制逻辑与上级任务调度集成。该COOptimization方案可以在底层网络基础架构上动态地计算最佳端到端虚拟路径。同时,它还可以通过从底层网络派生的信号调整上级网络的任务调度。仿真结果表明,我们所提出的方案在任务验收率,平均端到端延迟和网络负荷平衡程度方面优于传统方法。

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