• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus
  • Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
  • Chinese S&T Journal Citation Reports
  • Chinese Science Citation Database
Volume 54 Issue 5
Oct.  2019
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Article Contents
JIAN Jie, WANG Lide, NIE Xiaobo, SHEN Ping. Temporal Constraint Scheduling Algorithm for Periodic Data of Ethernet-Based Train Communication Network[J]. Journal of Southwest Jiaotong University, 2019, 54(5): 1113-1120. doi: 10.3969/j.issn.0258-2724.20180006
Citation: JIAN Jie, WANG Lide, NIE Xiaobo, SHEN Ping. Temporal Constraint Scheduling Algorithm for Periodic Data of Ethernet-Based Train Communication Network[J]. Journal of Southwest Jiaotong University, 2019, 54(5): 1113-1120. doi: 10.3969/j.issn.0258-2724.20180006

Temporal Constraint Scheduling Algorithm for Periodic Data of Ethernet-Based Train Communication Network

doi: 10.3969/j.issn.0258-2724.20180006
  • Received Date: 17 Jan 2018
  • Rev Recd Date: 30 May 2018
  • Available Online: 06 Jun 2018
  • Publish Date: 01 Oct 2019
  • Instead of time intervals as the only constraint in message scheduling for industrial Ethernet, a temporal constraint scheduling table generation method for periodic packet data of Ethernet-based train communication network (TCN) is proposed. Firstly, network and message model are modified by time-triggered mechanism. Secondly, a directed graph quantization model for periodic data was proposed according to temporal parameters both from communication equipments and transmitting packets. Finally, a scheduling table generation algorithm based on satisfiability modulo theory was designed. A scenario of unicast and multicast services was scheduled to verify effectiveness of the algorithm. The scheduling performance test and analysis were performed under the actual Ethernet TCN topology. Experimental results show that the proposed scheduling algorithm performs some scheduling tasks that traditional algorithms cannot do, provides a more detailed solution to scheduling requirements for periodic data, and improve scheduling flexibility. In the performance test, the maximum link load exceeds 80%, and its configurable process data traffic reaches 1 000 items.

     

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