Work-in-Progress: Probabilistic System-Wide DVFS for Real-Time Embedded Systems

Abstract

Nowadays, real-time embedded systems are facing concerns like power consumption and increased functionalities demand. Approaches based on Dynamic Voltage and Frequency Scaling (DVFS) reduce the energy consumed by processors while guaranteeing real-time constraints. In this paper, we present short-comings on existing models reducing energy consumption. Our experimental results clearly show that the execution time of tasks is not exclusively proportional to the processor speed. Thus, we believe that DVFS techniques could also be applied to other components like buses and memory. We discuss the applicability of a probabilistic Worst Case Execution Time (WCET) combined with DVFS techniques, and argue that by adopting a probabilistic frequency-aware model, we can (i) capture more detailed behaviors of tasks w.r.t. hardware frequencies and (ii) apply DVFS techniques to gain in energy consumption.