Managing Imprecise Worst Case Execution Times on DVFS Platforms

Although energy-efficient real-time task scheduling has attracted a lot of attention in the past decade, most existing results assumed deterministic execution lengths for tasks, or probabilistic lengths with a stable distribution. Such an assumption results in significant difficulty in their application to real problems. In this work, we relax this hypothesis by assuming that the worst case execution number of cycles (WCEC) might be imprecisely known. We present several methods to react to such a situation. We provide simulation results attesting that with a small effort, we can provide very good results, allowing to keep a low deadline miss rate as well as an energy consumption similar to clairvoyant algorithms. The main contribution of this work is to improve the robustness of low-power scheduling algorithms on DVFS (Dynamic Voltage and Frequency Scaling) frame-based platforms.