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Dynamic Resource Allocation Optimisation and Security-Resilient Control for Bandwidth-Limited Network Control Systems With Data Conflicts

  • Da Chen
  • , Kaibo Shi*
  • , Bin Guo
  • , Kangkang Sun
  • , Huaicheng Yan
  • , Xiao Cai*
  • *Corresponding author for this work
  • Chengdu University
  • College of Electrical Engineering
  • School of Astronautics, Harbin Institute of Technology
  • East China University of Science and Technology
  • Guangzhou University

Research output: Contribution to journalArticlepeer-review

Abstract

Networked control systems (NCSs) often suffer from performance degradation due to limited communication bandwidth, which can cause data transmission conflicts and packet loss. Existing scheduling strategies may fail to simultaneously meet the real-time requirements and the importance of multisensor data, and they are particularly vulnerable under distributed denial of service (DDoS) attacks. Firstly, to address these challenges, a greedy algorithm is proposed to optimise the data transmission process to satisfy the importance and real-time requirement of sensor data. It enables the dynamic allocation of network resources, reduces the possibility of data conflict and improves the communication efficiency. Then, an observer-based control algorithm is designed to ensure the system's stability and security resilience under bandwidth constraints and DDoS attacks. Therefore, in the face of packet loss caused by data conflict, the control algorithm can maintain efficient resource scheduling capability and improve the robustness of the system. Finally, the simulation results show that the proposed dynamic resource scheduling framework can guarantee the performance of NCSs under constrained network conditions.

Original languageEnglish
Pages (from-to)920-934
Number of pages15
JournalCAAI Transactions on Intelligence Technology
Volume11
Issue number3
DOIs
StatePublished - Jun 2026
Externally publishedYes

Keywords

  • cybersecurity
  • greedy algorithm
  • lyapunov theory
  • network control systems
  • observer-based control

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