Maintaining temporal consistency of real-time data is important for cyber-physical systems. Most of the previous studies focus on uniprocessor systems. In this paper, the problem of temporal consistency maintenance on multiprocessor platforms with instance skipping was formulated based on the (m,k)-constrained model. A partitioned scheduling method SC-AD was proposed to solve the problem. SC-AD uses a derived sufficient schedulability condition to calculate the initial value of m for each sensor transaction. It then partitions the transactions among the processors in a balanced way. To further reduce the average relative invalid time of real-time data, SC-AD judiciously increases the values of m for transactions assigned to each processor. Experiment results show that SC-AD outperforms the baseline methods in terms of the average relative invalid time and the average valid ratio under different system workloads.

保持实时数据的时间一致性对于网络物理系统很重要。先前的大多数研究都集中在单处理器系统上。本文基于（m，k）约束模型，提出了带实例跳过的多处理器平台时间一致性维护问题。为了解决该问题，提出了一种分区调度方法SC-AD。SC-AD使用派生的足够的可调度性条件来计算每个传感器事务的m的初始值。然后，它以平衡的方式在处理器之间划分事务。为了进一步减少实时数据的平均相对无效时间，SC-AD明智地增加了m的值。用于分配给每个处理器的交易。实验结果表明，在不同系统工作负载下，SC-AD的平均相对无效时间和平均有效比率优于基线方法。