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

机译:用于实时数据质量维护的传感器事务的多处理器调度

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摘要

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.
机译:在网络物理系统中,应有效地调度传感器事务以维持实时数据对象的时间有效性。以前关于传感器交易调度的研究主要关注单处理器系统。在本文中,我们研究了多处理器平台上的数据质量的调度问题问题。数据质量被定义为描述实时数据对象的有效程度。提出了两种命名为质量最大化(P-QM)和改进的P-QM调度(IP-QM)的分区调度的方法。 P-QM通过明智地确定每个传感器事务的预分配计算时间来最大化数据质量,并将事务分配给不同的处理器。 IP-QM通过基于系统的当前状态,通过自适应地在每个处理器上自适应地执行事务实例来提高从P-QM获得的数据质量。通过实验证明IP-QM可以在不同的系统工作负载下提供比P-QM更高的数据质量。

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