In cyber-physical systems, sensor transactions should be effectively scheduled to maintain the temporal validity of real-time data\nobjects. Previous studies on sensor transaction scheduling mainly focus on uniprocessor systems. In this paper, we study the\nproblem of data quality-based scheduling of sensor transactions on multiprocessor platforms. The data quality is defined to\ndescribe the validity degree of real-time data objects. Two methods, named the Partitioned Scheduling for Quality Maximization\n(P-QM) and the improved P-QM scheduling (IP-QM), are proposed. P-QM maximizes the data quality by judiciously determining\nthe preallocated computation time of each sensor transaction and assigns the transactions to different processors. IPQM\nimproves the data quality obtained from P-QM by adaptively executing transaction instances on each processor based on the\ncurrent status of the system. It is demonstrated through experiments that IP-QM can provide higher data quality than P-QM\nunder different system workloads.
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