During execution, activity durations may vary from those predicted in the generated schedule. In this article we study (re) scheduling invocation, execution during rescheduling, and flexible execution to enable a high level of responsiveness to uncertainty in activity execution duration. We discuss these methods theoretically in the context of an embedded scheduler and practically in the context of a limited CPU embedded scheduler with a nonzero scheduler runtime intended for a planetary rover.

We use the concept of a commit window to enable execution of the previously generated schedule while (re) scheduling. We define Fixed Cadence and Event Driven scheduling as methods to decide when to reinvoke the scheduler. We define and analyze Flexible Execution (FE) as an approach to execute the generated schedule while adapting it to variations in execution. Specifically, FE focuses on (1) how to take advantage of activities ending earlier than expected and (2) how to maintain a consistent schedule if activities take more time than expected. We present a theoretical model and empirical results documenting how these various methods interact and perform on both synthetic data and best available data for NASA’s next planetary rover, the Mars 2020 rover. We then describe how these analyses influenced the onboard software for the Mars 2020 rover.

在执行期间，活动持续时间可能会与生成的计划中预测的持续时间有所不同。在本文中，我们研究（重新）安排调用，重新安排期间的执行以及灵活的执行，以实现对活动执行持续时间不确定性的高度响应。我们理论上在嵌入式调度程序的上下文中讨论这些方法，而实际上在有限的CPU嵌入式调度程序的上下文中讨论这些方法，该调度程序用于行星漫游车的非零调度程序运行时。

我们使用提交窗口的概念来启用（重新）调度时先前生成的调度的执行。我们将固定节奏和事件驱动计划定义为确定何时重新调用计划程序的方法。我们定义并分析弹性执行（FE）作为一种执行生成的计划，同时使其适应执行变化的方法。具体来说，富裕关注（1）如何利用活动早于预期结束的活动；（2）如果活动花费的时间比预期多，如何保持一致的进度。我们提供了理论模型和实证结果，记录了这些各种方法如何相互作用以及如何在NASA的下一个行星火星探测器“火星2020”火星车的合成数据和最佳可用数据上进行交互。然后，我们描述这些分析如何影响2020年火星探测器的车载软件。