The execution time of conventional incremental off-line schedule approaches for time-triggered networks increases rapidly when networks become larger. When the traffic in a network changes, they need to reschedule all influenced flows once again. Traffic changes at the cluster level involve many data flows. An incremental scheduler cannot react quickly to such changes. We propose an algorithm based on mixed integer linear programming and counterexample guided methodology. Our algorithm can generate adaptive schedule for cluster-level changes of the system. The adaptive schedule can react quickly to the changes during runtime. Our algorithm enhances the incremental schedulers. It allows schedulers to react to changing at both the flow level and the cluster level. Experiments show that our approach is effective. In the scenarios of coupling train consists, our algorithm can generate the schedule table of the train network within a few seconds.

中文翻译：

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多集群时间触发列车通信网络的自适应调度


当网络变得更大时，时间触发网络的传统增量离线调度方法的执行时间迅速增加。当网络中的流量发生变化时，他们需要再次重新调度所有受影响的流量。集群层面的流量变化涉及到很多数据流。增量调度程序无法对此类变化做出快速反应。我们提出了一种基于混合整数线性规划和反例引导方法的算法。我们的算法可以为系统的集群级变化生成自适应调度。自适应调度可以对运行时的变化做出快速反应。我们的算法增强了增量调度程序。它允许调度程序对流级别和集群级别的变化做出反应。实验表明我们的方法是有效的。在耦合列车组成的场景中，我们的算法可以在几秒钟内生成列车网络的时刻表。