Real-Time Transmission Optimization for Edge Computing in Industrial Cyber-Physical Systems

Yuhuai Peng, Alireza Jolfaei, Qiaozhi Hua, Wen-Long Shang, Keping Yu

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)

Abstract

With the rapid development of Industry 4.0, the industrial cyber-physical systems (ICPS) are expected to realize the digital sensing, automatic control, and refined management in smart factories. However, limited bandwidth resources and severe industrial interference make it difficult to meet the real-time and ultrahigh reliability in edge computing (EC)-based next-generation industrial automation networks. To tackle these challenges, in this article, we propose a real-time transmission optimization scheme to accelerate EC. First, we establish a hierarchical system model for smart manufacturing and automation scenarios. Then we present a power control optimization method based on noncooperative game to alleviate interference and reduce energy consumption. Finally, we propose a path optimization scheme based on Q-learning for low-latency and ultrahigh reliability transmission requirements. Extensive simulation results reveal that our proposals perform better in terms of transmission delay and packet-loss rate compared with traditional methods, and therefore, contributes to EC deployment in ICPS.

Original languageEnglish
Pages (from-to)9292-9301
Number of pages10
JournalIEEE Transactions on Industrial Informatics
Volume18
Issue number12
Early online date9 Jun 2022
DOIs
Publication statusPublished - Dec 2022

Keywords

  • Edge computing (EC)
  • industrial cyber-physical systems (ICPS)
  • noncooperative game (NG-PCO)
  • power control
  • real-time transmission
  • smart factories

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