期刊
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
卷 17, 期 5, 页码 3143-3152出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2020.3010983
关键词
Task analysis; Job shop scheduling; Optimal scheduling; Control systems; Routing; Dynamic scheduling; Informatics; Cyber– physical system (CPS); path allocation; software defined networking (SDN); task scheduling
类别
资金
- Natural Science Foundation of Hubei Province [2019CFB138, 2018CFB346]
- National Science Foundation of China [61625305]
A cooptimization method based on software defined networking technology is proposed to enhance the performance of task scheduling and network communication in large and complex engineering systems. Simulation results show the proposed scheme outperforms the traditional method in terms of task acceptance rate, average end-to-end delay, and network load balance degree.
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.
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