Multiprocessor Scheduling of Sensor Transactions for Real-Time Data Quality Maintenance

Abstract EN

In cyber-physical systems, sensor transactions should be effectively scheduled to maintain the temporal validity of real-time data objects.

Previous studies on sensor transaction scheduling mainly focus on uniprocessor systems.

In this paper, we study the problem of data quality-based scheduling of sensor transactions on multiprocessor platforms.

The data quality is defined to describe the validity degree of real-time data objects.

Two methods, named the Partitioned Scheduling for Quality Maximization (P-QM) and the improved P-QM scheduling (IP-QM), are proposed.

P-QM maximizes the data quality by judiciously determining the preallocated computation time of each sensor transaction and assigns the transactions to different processors.

IP-QM improves the data quality obtained from P-QM by adaptively executing transaction instances on each processor based on the current status of the system.

It is demonstrated through experiments that IP-QM can provide higher data quality than P-QM under different system workloads.