Towards adaptive hierarchical scheduling of overloaded real-time systems

N. Khalilzad, Thomas Nolte, M. Behnam
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引用次数: 5

Abstract

In a hierarchical scheduling framework, a resource can be shared among modules with different criticality levels. In our recently introduced adaptive hierarchical scheduling framework, modules receive a dynamic portion of the CPU during run-time. While providing temporal isolation is one of the main advantages of hierarchical scheduling, in an adaptive framework, for example when the CPU is overloaded, the higher priority modules can violate timing guarantees of the lower priority modules. However, the priorities of modules are assigned based on parameters other than the module criticality levels. For example the priority is often assigned according to periods and deadlines of tasks to increase the CPU utilization assuming static systems, i.e. modules parameters do not change during runtime. In an overload situation the high criticality modules should be superior to the low criticality modules in receiving resources. In this paper, extending our adaptive framework, we propose two techniques for controlling the CPU distribution among modules in an overload situation. We are taking another step towards having a complete adaptive hierarchical scheduling framework by incorporating an overload controller into our framework.
超载实时系统的自适应分层调度研究
在分层调度框架中,资源可以在不同临界级别的模块之间共享。在我们最近引入的自适应分层调度框架中,模块在运行时接收CPU的动态部分。虽然提供时间隔离是分层调度的主要优点之一,但在自适应框架中,例如当CPU过载时,高优先级模块可能会违反低优先级模块的定时保证。但是,模块的优先级是根据模块临界级别以外的参数分配的。例如,优先级通常根据任务的周期和截止日期分配,以增加CPU利用率,假设静态系统,即模块参数在运行时不改变。在过载情况下,高临界模块接收资源的能力应优于低临界模块。在本文中,我们扩展了我们的自适应框架,提出了在过载情况下控制模块间CPU分配的两种技术。通过在我们的框架中加入一个过载控制器,我们朝着拥有一个完整的自适应分层调度框架又迈出了一步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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