Hierarchical scheduling provides predictable timing and temporal isolation; two properties desirable in real-time embedded systems. In hierarchically scheduled systems, subsystems should receive a sufficient amount of CPU resources in order to be able to guarantee timing constraints of its internal parts (tasks). In static systems, an exact amount of CPU resource can be allocated to a subsystem. However, in dynamic systems, where execution times of tasks vary considerably during runtime, it is desirable to give a dynamic portion of the CPU given the current load situation. In this paper we present a feedback control approach for adapting the amount of CPU resource that is allocated to subsystems during run-time such that each subsystem receives sufficient resources while keeping the number of deadline violations to a minimum. We also show an example simulation where the controller adapts the budget of a subsystem.

Hierarchical scheduling provides a modular framework for integrating, scheduling and guaranteeing timing constraints of compositional real-time systems. In such a scheduling framework, all modules should receive a sufficient portion of the shared CPU to be able to guarantee timing constraints of their internal parts. In dynamic systems i.e., systems where the execution time of tasks are subjected to sudden and drastic changes during run-time, assigning fixed CPU portions to the modules is conducive to either low CPU utilization or numerous task deadline misses. In this paper, in order to address this problem, we propose an adaptive CPU allocation method which dynamically assigns CPU portions to the modules during run-time based on their current CPU demand. Besides, the presented approach is evaluated using a series of different simulations. In addition, we present a method for scheduling modules in situations when the CPU resource is not sufficient for scheduling all modules. We introduce the notion of module (subsystem) criticality, and in an overload situation we distribute the CPU resource based on the criticality of modules.