Journal of Systems Engineering and Electronics ›› 2022, Vol. 33 ›› Issue (4): 792-804.doi: 10.23919/JSEE.2022.000079

• CLOUD CONTROL SYSTEMS • Previous Articles     Next Articles

Distributed point-to-point routing method for tasks in cloud control systems

Guan WANG1,2(), Yufeng ZHAN1(), Yuanqing XIA1(), Liping YAN1,*()   

  1. 1 School of Automation, Beijing Institute of Technology, Beijing 100081, China
    2 School of Information Science and Engineering, Zaozhuang University, Zaozhuang 277100, China
  • Received:2022-03-01 Online:2022-08-30 Published:2022-08-30
  • Contact: Liping YAN;;;
  • About author:|WANG Guan was born in 1986. He received his M.S. degree in computer science and technology from University of Ji’nan, China, in 2014. He is currently working toward his Ph.D. degree in the School of Automation, Beijing Institute of Technology, China. He was a lecturer in the School of Information Science and Engineering, University of Zaozhuang, China in 2019. His research interests include networking systems, cloud computing, gene expression data, and machine learning. E-mail:||ZHAN Yufeng was born in 1989. He received his Ph.D. degree from Beijing Institute of Technology (BIT), Beijing, China, in 2018. He is currently an assistant professor in the School of Automation with BIT. Prior to joining BIT, he was a post-doctoral fellow in the Department of Computing with The Hong Kong Polytechnic University. His research interests include networking systems, game theory, and machine learning. E-mail:||XIA Yuanqing was born in 1971. He received his Ph.D. degree in control theory and control engineering from Beijing University of Aeronautics and Astronautics, Beijing, China, in 2001. From January 2002 to November 2003, he was a postdoctoral research associate with the Institute of Systems Science, Academy of Mathematics and System Sciences, Chinese Academy of Sciences, Beijing, China. From November 2003 to February 2004, he was with National University of Singapore as a research fellow, where he worked on variable structure control. From February 2004 to February 2006, he was with University of Glamorgan, Pontypridd, U.K., as a research fellow. From February 2007 to June 2008, he was a guest professor with Innsbruck Medical University, Innsbruck, Austria. Since 2004, he has been with School of Automation, Beijing Institute of Techno-logy, Beijing, first as an associate professor, then, since 2008, as a professor. His research interests include networked control systems, robust control and signal processing, and active disturbance rejection control. E-mail:||YAN Liping was born in 1979. She received her B.S. and M.S. degrees in mathematics from Henan University, Kaifeng, China, in 2000 and 2003, respectively, and Ph.D. degree in control science and engineering from Tsinghua University, Beijing, China, in 2007. From 2007 to 2009, she was a postdoctoral research associate with the Equipment Academy of Air Force, Beijing. Since 2009, she has been with the School of Automation, Beijing Institute of Technology, Beijing, first as an assistant professor, from 2011 to 2021 as an associate professor, and then, since 2021, as a full professor. From 2012 to 2013, supported by China Scholarship Council, she was a visiting scholar with the University of New Orleans, New Orleans, Louisiana, USA. From September 2018 to August 2019, she was a visiting scholar with the University of Windsor, Windsor, Ontario, Canada. Her research interests include multisensor data fusion, target tracking, fault detection, image registration, intelligent navigation, and integrated navigation. E-mail:
  • Supported by:
    This work was supported by the National Key Research and Development Program of China (2018AAA0103203), the National Natural Science Foundation of China (62073036;61836001;62102022;62122014), and the Beijing Natural Science Foundation of China (42020741).


With the rapid development of cloud computing and control theory, a new paradigm of networked control systems called cloud control systems is proposed to meet the requirements of large-scale and complex applications. Currently, cloud control systems are mainly built by using a centralized architecture. The centralized system is overly dependent on the central control plane and has huge challenges in large-scale heterogeneous node systems. In this paper, we propose a decentralized approach to establish cloud control systems by proposing a distributed point-to-point task routing method. A considerable number of tasks in the system will not rely on the central plane and will be directly routed to the target devices through the point-to-point routing method, which improves the horizontal scalability of the cloud control system. The point-to-point routing method directly gives a unique address to every task, making inter-task communication more efficient in a complex heterogeneous and busy cloud control systems. Finally, we experimentally demonstrate that the distributed point-to-point task routing approach is compatible against the state-of-the-art central systems in large-scale task situations.

Key words: cloud control system, task routing, cloud-edge-device cooperation