Dual-Network Task Scheduling inCyber–Physical Systems: A Cooptimization Approach

Abstract

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.