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Adaptive co-scheduling for periodic application and update transactions in real-time database systems

机译:自适应协同调度,用于实时数据库系统中的定期应用程序和更新事务

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In this paper, we study the co-scheduling problem of periodic application transactions and update trans actions in real-time database systems for surveillance of critical events. To perform the surveillance functions effectively, it is important to meet the deadlines of the application transactions and maintain the quality of the real-time data objects for their executions. Unfortunately, these two goals are con flicting and difficult to be achieved at the same time. To address the co-scheduling problem, we propose a real-time co-scheduling algorithm, called Adaptive Earliest Deadline First Co-Scheduling (AEDF-Co). In AEDF-Co, a dynamic scheduling approach is adopted to adaptively schedule the update and application jobs based on their deadlines. The performance goal of AEDF-Co is to determine a schedule for given sets of periodic application and update transactions such that the deadline constraints of all the application transactions are satisfied and at the same time the quality of data (QoD) of the real-time data objects is maximized. Extensive simulation experiments have been performed to evaluate the performance of AEDF-Co. The results show that by adaptively adjusting the release times of update jobs and scheduling the update and application jobs dynamically based on their urgencies, AEDF-Co is effective in achieving the performance goals and maximizing the overall system performance.
机译:在本文中,我们研究了定期应用程序事务的协同调度问题,并在实时数据库系统中更新事务以监视关键事件。为了有效执行监视功能,重要的是要满足应用程序事务的截止日期并保持实时数据对象的执行质量。不幸的是,这两个目标是矛盾的,很难同时实现。为了解决协同调度问题,我们提出了一种实时协同调度算法,称为自适应最早截止时间优先协同调度(AEDF-Co)。在AEDF-Co中,采用动态调度方法来根据更新和应用程序的截止日期自适应地调度更新和应用程序作业。 AEDF-Co的性能目标是为给定的定期应用程序集确定时间表,并更新交易,以便满足所有应用程序交易的截止日期约束,并同时满足实时数据质量(QoD)数据对象已最大化。已经进行了广泛的模拟实验以评估AEDF-Co的性能。结果表明,AEDF-Co通过自适应地调整更新作业的发布时间并根据其紧急程度动态安排更新和应用程序作业,可以有效地实现性能目标并最大限度地提高整体系统性能。

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