| 列车通信以太网周期数据时态约束调度方法 |
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| 引用本文： | 简捷,王立德,聂晓波,申萍.列车通信以太网周期数据时态约束调度方法[J].西南交通大学学报,2019,54(5):1113-1120. |
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| 作者姓名： | 简捷 王立德 聂晓波 申萍 |
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| 基金项目： | 中国铁路总公司科技研究开发计划课题（2017J008-K） |
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| 摘 要： | 针对工业以太网调度方法以报文截止期为唯一约束的局限，提出了一种基于时态约束的列车通信网络周期数据调度表生成方法.首先基于时间触发机制改造列车以太网的通信与消息模型；其次利用网络设备通信参数与数据报文参数，提出周期数据通信的时态约束有向图量化模型；最后设计了基于可满足性模理论的调度表生成算法，求解单播及广播业务的周期数据调度表以验证算法有效性，并在实际列车通信网络的拓扑条件下进行调度性能测试及分析.实验结果表明:该调度算法能够解决部分传统算法不能调度的通信任务，满足更细化的周期数据调度需求并提升调度灵活性；调度性能测试中最大链路负载超过80%，可调度周期数据业务量达到1 000项.
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| 关 键 词： | 通信网络 调度方法 实时系统 以太网 |
| 收稿时间： | 2018-01-17 |
Temporal Constraint Scheduling Algorithm for Periodic Data of Ethernet-Based Train Communication Network |
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| 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. |
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| Authors: | JIAN Jie WANG Lide NIE Xiaobo SHEN Ping |
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| Abstract: | 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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