Optimal Two-Level Speed Assignment for Real-Time Systems

Reducing energy consumption is one of the main concerns in the design and implementation of embedded real-time systems. For this reason, the current generation of processors allows to vary voltage and operating frequency to balance computational speed and energy consumption. This technique is called dynamic voltage scaling (DVS). When applying DVS tohard real-time systems, it is important to provide the worst-case computational requirement; otherwise the timing constraints may be violated. However, the probability of a task executing for its worst-case execution time is very low. In this paper,we show how to exploit probabilistic information about the execution time of a task in order to reduce the energy consumed by the processor. Optimal speed assignments and transition points are found using a very general model for the processor. The model accounts for the processor idle power and time/energy overheads due to frequency transitions. We also show how these results apply to some significant cases

Dynamic Voltage Scaling for Energy- Constrained Real-Time Systems

The problem of reducing energy consumption is dominating the design of several real-time systems. The Dynamic Voltage Scaling (DVS) technique, provided by most microprocessors, allow to balance computational speed versus energy consumption. We present some novel energy-aware scheduling algorithms that allow to expoit this technique while meeting real-time constraints. In particular, we present the GRUB-PA algorithm which, unlike most existing algorithms, allows to reduce energy consumption on real-time systems consisting of any kind of task. We also present a working implementation of the algorithm on Linux