We consider the problem of resource provisioning for real-time cyber-physical applications in an open system environment where there does not exist a global resource scheduler that has complete knowledge of the real-time performance requirements of each individual application that shares the resources with the other applications. Regularity-based Resource Partition (RRP) model is an effective strategy to hierarchically partition and assign various resource slices among the applications. However, RRP model does not consider changes in resource requests from the applications at run time. To allow for the run time adaptation to resource requirement changes, we consider in this paper the issues in online resource partition reconfiguration, including semantics issues that arise in configuration transitions that may cause application failures. Based on the reconfiguration semantics, we study the online resource reconfigurability problem under the RRP model where the availability factors of resource partitions may be reconfigured at run time. We formalize and solve the Dynamic Partition Reconfiguration (DPR) problem for uniform environment where the minimal intervals assigned to each task for execution on each resource are the same. Extensive experiments have been conducted to evaluate the performance of the proposed approaches in different scenarios. We also present a case study using the autonomous F1/10 model car; the controller of the F1/10 car requires resource adaptation to satisfy the computing needs of its PID controller and vision system under different operating conditions. Our implementation demonstrates the effectiveness and benefit of online resource partition reconfiguration using the proposed approach in a real-world cyber-physical system.

我们考虑在不存在全局资源调度程序的开放系统环境中为实时网络物理应用程序配置资源的问题，该全局资源调度程序完全了解与共享资源的每个单独应用程序的实时性能要求。其他应用程序。基于规则的资源分区（RRP）模型是一种有效的策略，可以在应用程序之间进行分层分区并分配各种资源片。但是，RRP模型不考虑运行时来自应用程序的资源请求中的更改。为了允许运行时适应资源需求的变化，我们在本文中考虑在线资源分区重新配置中的问题，包括在配置转换中出现的语义问题，可能会导致应用程序故障。基于重新配置的语义，我们研究了RRP模型下的在线资源可重新配置性问题，其中在运行时可以重新配置资源分区的可用性因素。我们形式化并解决针对统一环境的动态分区重新配置（DPR）问题，其中分配给每个任务以在每个资源上执行的最小间隔是相同的。已经进行了广泛的实验，以评估所提出的方法在不同情况下的性能。我们还介绍了使用自动F1 / 10模型汽车的案例研究；F1 / 10汽车的控制器需要进行资源调整，以满足其PID控制器和视觉系统在不同工况下的计算需求。我们的实现演示了在实际的网络物理系统中使用建议的方法进行在线资源分区重新配置的有效性和好处。