Crown scheduling is a static scheduling approach for sets of parallelizable tasks with a common deadline, aiming to minimize energy consumption on parallel processors with frequency scaling. We demonstrate that crown schedules are robust, i. e. that the runtime prolongation of one task by a moderate percentage does not cause a deadline transgression by the same fraction. In addition, by speeding up some tasks scheduled after the prolonged task, the deadline can still be met at a moderate additional energy consumption. We present a heuristic to perform this re-scaling online and explore the tradeoff between additional energy consumption in normal execution and limitation of deadline transgression in delay cases. We evaluate our approach with scheduling experiments on synthetic and application task sets. Finally, we consider influence of heterogeneous platforms such as ARM’s big.LITTLE on robustness.

Crown调度是针对具有公共截止日期的可并行化任务集的静态调度方法，旨在通过频率缩放将并行处理器的能耗降至最低。我们证明皇冠计划是可靠的，即 e。一项任务的运行时间延长适当的百分比不会导致最后期限的违约次数减少。此外，通过加快在延长任务后安排的某些任务，仍可以以适度的额外能耗满足最后期限。我们提出一种启发式方法来在线执行此重新缩放，并探索正常执行中的额外能耗与延迟情况下的截止期限违规限制之间的权衡。我们通过在合成和应用任务集上安排实验来评估我们的方法。最后，