Weakly-hard real-time scheduling enables to tolerate certain execution timeouts of tasks, and has been widely exploited in those intelligent embedded systems over the past two decades. In general, the current weakly-hard real-time scheduling algorithms try to rapidly raise the priorities of jobs (instances) of those tasks that have missed deadlines to guarantee their individual weakly-hard constraints, while neglecting the impacts of whole task system emergency on the schedulability results. From the perspective of increasing the schedulability ratio of weakly-hard real-time task set upon a uniprocessor platform, we develop a Global Emergency-Based Scheduling (GEBS) algorithm. First, with the goal of guaranteeing the weakly-hard timeliness of jobs, the GEBS scheme formulates a set of global job-level policies for priority allocations based on the emergency-classes of jobs. With the emergency degree of whole task system being considered, GEBS intends to fairly tune the priorities of those urgent jobs following our priority adjustment scheme to reduce the possibility of dynamic failures (i.e., deadline misses) of jobs. Moreover, for a task, the minimum arrival-interval of two jobs that have the same emergency-class is thoroughly analyzed, and then its WCRT (Worst-Case Response Time) corresponding to each emergency-class can be obtained recursively. Furthermore, the schedulability test is discussed based on the WCRT analysis, followed by the investigation of a new LCM (Least Common Multiple)-based method under weakly-hard constraints for better feasibility of task set. Finally, the extensive results from simulations and case study demonstrate that the GEBS algorithm can effectively improve the schedulability performance with regard to acceptance ratio (e.g., 50% more) with acceptable running time, when compared to the existing task-level and job-class-level scheduling. The empirical results in Linux kernel further exhibit the applicability of GEBS that can experience comparable online overhead in contrast with other schemes.

弱硬的实时调度可以容忍某些任务的执行超时，并且在过去的二十年中已被那些智能嵌入式系统广泛采用。总的来说，当前的弱硬实时调度算法试图迅速提高那些错过最后期限的任务的工作（实例）的优先级，以保证其各自的弱硬约束，同时又忽略了整个任务系统紧急情况对工作的影响。可调度性结果。从提高单处理器平台上的弱硬实时任务集的可调度性的角度出发，我们开发了一种基于全局紧急事件的调度（GEBS）算法。首先，为了保证工作的及时性，GEBS计划制定了一套全球性的计划。作业级策略，用于根据作业的紧急情况类别分配优先级。考虑到整个任务系统的紧急程度，GEBS打算按照我们的优先级调整方案合理调整那些紧急工作的优先级，以减少工作动态失败（即截止期限）的可能性。此外，对于一项任务，将彻底分析具有相同紧急级别的两个作业的最小到达间隔，然后可以递归获得与每个紧急级别相对应的WCRT（最坏情况响应时间）。此外，基于WCRT分析讨论了可调度性测试，然后研究了一种基于LCM（最小公倍数）的新方法在弱硬约束下可以更好地完成任务集。最后，来自仿真和案例研究的大量结果表明，与现有任务级别和工作类别相比，GEBS算法可以在可接受的运行时间上有效地提高接受率（例如，提高50％）的可调度性。级调度。Linux内核中的经验结果进一步展示了GEBS的适用性，与其他方案相比，GEBS可以承受相当的在线开销。