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Load regulating algorithm for static-priority task scheduling on multiprocessors

机译:多处理器上静态优先级任务调度的负载调节算法

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This paper proposes a fixed-priority partitioned scheduling algorithm for periodic tasks on multiprocessors. A new technique for assigning tasks to processors is developed and the schedulability of the algorithm is analyzed for worst-case performance. We prove that, if the workload (utilization) of a given task set is less than or equal to 55.2% of the total processing capacity on m processors, then all tasks meet their deadlines. During task assignment, the total work load is regulated to the processors in such a way that a subset of the processors are guaranteed to have an individual processor load of at least 55.2%. Due to such load regulation, our algorithm can be used efficiently as an admission controller for online task scheduling. And this online algorithm is scalable with increasing number of cores in chip multiprocessors. In addition, our scheduling algorithm possesses two properties that may be important for the system designer. The first one guarantees that if task priorities are fixed before task assignment they do not change during task assignment and execution, thereby facilitating debugging during development and maintenance of the system. The second property guarantees that at most m/2 tasks are split, thereby keeping the run-time overhead as caused by task splitting low.
机译:本文提出了一种固定优先级分区调度算法,用于多处理器上的周期性任务。开发了一种用于为处理器分配任务的新技术,分析了算法的调度性以获得最坏情况性能。我们证明,如果给定任务集的工作负载(利用率)小于或等于M处理器上总处理容量的55.2%,则所有任务都会符合其截止日期。在任务分配期间,以这样的方式调节总工作负载,使得处理器的子集被保证具有至少55.2%的单个处理器负载。由于这种载荷调节,我们的算法可以有效地用作用于在线任务调度的准入控制器。而且该在线算法可延长芯片多处理器数量的核心数量。此外,我们的调度算法具有两个可能对系统设计者很重要的属性。第一个保证,如果任务分配在任务分配之前修复任务优先级,则在任务分配和执行期间不会更改,从而在系统开发和维护期间促进调试。第二个属性保证,在大多数M / 2任务中被分开,从而保持运行时开销,因为由任务分割低电平造成的。

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