Temporal consistency maintenance on multiprocessor platforms with instance skipping

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.