A Hierarchical Data Transmission Framework for Industrial Wireless Sensor and Actuator Networks

Xi Jin, Fanxin Kong, Linghe Kong, Huihui Wang, Changqing Xia, Peng Zeng, Qingxu Deng

Research output: Contribution to journalArticlepeer-review

42 Scopus citations


A smart factory generates vast amounts of data that require transmission via large-scale wireless networks. Thus, the reliability and real-time performance of large-scale wireless networks are essential for industrial production. A distributed data transmission scheme is suitable for large-scale networks, but is incapable of optimizing performance. By contrast, a centralized scheme relies on knowledge of global information and is hindered by scalability issues. To overcome these limitations, a hybrid scheme is needed. We propose a hierarchical data transmission framework that integrates the advantages of these schemes and makes a tradeoff among real-time performance, reliability, and scalability. The top level performs coarse-grained management to improve scalability and reliability by coordinating communication resources among subnetworks. The bottom level performs fine-grained management in each subnetwork, for which we propose an intrasubnetwork centralized scheduling algorithm to schedule periodic and aperiodic flows. We conduct both extensive simulations and realistic testbed experiments. The results indicate that our method has better schedulability and reduces packet loss by up to 22% relative to existing methods.

Original languageEnglish (US)
Article number7885069
Pages (from-to)2019-2029
Number of pages11
JournalIEEE Transactions on Industrial Informatics
Issue number4
StatePublished - Aug 2017
Externally publishedYes


  • Data flow scheduling
  • hierarchical data transmission framework
  • resource coordination

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Computer Science Applications
  • Electrical and Electronic Engineering


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