随着轨道交通智能化的发展,列车控制与监测产生的高带宽实时数据对列车通信网络提出了更高的要求.时间敏感网络可作为兼具高传输速率、高确定性和高兼容性的下一代列车通信网络解决方案.然而,实现时间敏感网络确定性通信机制的流量门控调度设计难以拓展到实际场景规模.因此,针对车载网络流量特性,提出一种基于改进增量式调度策略和改进灰狼优化算法的列车通信网络流量门控调度生成方法.首先,基于列车通信网络流量和拓扑结构建立门控调度系统模型.然后,为提高调度生成效率,提出了基于增量式调度的单帧简易调度(Single Frame Simple Scheduling,SFSS)策略,弥补了门控调度模型在计算速度方面的不足.其次,为提高灰狼优化算法的寻优性能,引入了粒子群优化算法、Logistic混沌映射策略和反正切函数,提出了改进灰狼优化(Improved Grey Wolf Optimization,IGWO)算法,改善了实时周期性流量的实时性能和带宽占用.最后,利用SFSS策略和IGWO算法对列车通信网络门控调度系统模型进行测试和求解,通过实验验证所提出调度生成方法的可行性和有效性.实验结果表明,与其他方法相比,提出的门控调度生成方法在计算精度和计算速度方面具有更大的优势,流量调度的平均端到端时延降低为57 μs.研究成果能够满足列车通信网络流量调度的需求,可有效地实现时间敏感网络确定性通信在列车中的应用和改善.
Real-time traffic scheduling optimization of train communication network based on time-sensitive network
With the development of intelligent rail transit,the massive real-time data generated by train control and monitoring puts forward higher demand for train communication network.Time-sensitive network can be used as the next-generation train communication network solution with high transmission rate,high determinism and high compatibility.However,the traffic gating scheduling design of time-sensitive network deterministic communication mechanism is difficult to scale up to practical scenarios.Therefore,aiming at the traffic characteristics of in-vehicle networks,a traffic gating scheduling generation method based on improved incremental scheduling strategy and improved gray wolf optimization(IGWO)algorithm for train communication networks was proposed.Firstly,a gating scheduling system model was established based on the traffic and topology of train communication network.Secondly,in order to improve the efficiency of schedule generation,a single frame simple scheduling(SFSS)strategy based on incremental scheduling was proposed to make up for the shortcomings of the gating scheduling model in computing speed.Then,in order to improve the optimization performance of grey wolf optimization algorithm,particle swarm optimization algorithm,Logistic chaos mapping strategy and arctangent function were introduced,and IGWO algorithm was proposed,improving the real-time performance and bandwidth usage of real-time periodic traffic.Finally,SFSS strategy and IGWO algorithm were used to test and solve the gating scheduling system model of train communication network,and the feasibility and effectiveness of the proposed schedule generation method were verified by experiments.Experimental results show that the proposed gating schedule generation method has greater advantages in computation accuracy and computation speed comparing with other methods,reducing the average end-to-end delay to 57 μs.The research results can meet the demand of traffic scheduling in train communication network and effectively realize the application and improvement of deterministic communication of time-sensitive network in trains.
train communication networktime-sensitive networktraffic schedulingincremental schedulingimproved grey wolf optimization
万方数据
维普
