Adaptive hierarchical scheduling framework: Configuration and evaluation

We have introduced an adaptive hierarchical scheduling framework as a solution for composing dynamic realtime systems, i.e., systems where the CPU demand of its tasks are subjected to unknown and potentially drastic changes during runtime. The framework consists of a controller which periodically adapts the system to the current load situation. In this paper, we unveil and explore the detailed behavior and performance of such an adaptive framework. Specifically, we investigate the controller configurations enabling efficient control parameters which maximizes performance, and we evaluate the adaptive framework against a traditional static one. Furthermore, we demonstrate the results of our investigation using a practical multimedia case study in which we simulate the timing behavior of video decoding tasks running on our proposed framework. In addition, we compare the results of using our framework with the results of using static resource allocation approach.