A dynamic voltage scaling algorithm for energy reduction in hard real-time systems
Van R. Culver, Sunil P. Khatri
Abstract
Van R. Culver, Sunil P. Khatri
Abstract
As the quantity and functional complexity of battery powered portable devices continues to rise, energy efficient design of such devices has become increasingly important. Many real-time scheduling algorithms have been developed recently to reduce energy consumption in hard real-time embedded systems that use dynamic voltage scaling (DVS) capable processors. This paper explores an algorithm that seeks to reduce energy consumption by considering tasks in tandem, with the intuition that what may be a good frequency for one task, may be much worse for another. In particular, our algorithm considers pairs of tasks, and optimizes them simultaneously so that their total energy consumption is minimized while all deadlines are met. Experimental results demonstrate that our method is able to effectively improve on the results of look-ahead EDF, one of the best energy-aware schedulers, especially for task sets with moderate utilization, and "harmonious" task periodicity.
OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
As the quantity and functional complexity of battery powered portable devices continues to rise, energy efficient design of such devices has become increasingly important. Many real-time scheduling algorithms have been developed recently to reduce energy consumption in hard real-time embedded systems that use dynamic voltage scaling (DVS) capable processors. This paper explores an algorithm that seeks to reduce energy consumption by considering tasks in tandem, with the intuition that what may be a good frequency for one task, may be much worse for another. In particular, our algorithm considers pairs of tasks, and optimizes them simultaneously so that their total energy consumption is minimized while all deadlines are met. Experimental results demonstrate that our method is able to effectively improve on the results of look-ahead EDF, one of the best energy-aware schedulers, especially for task sets with moderate utilization, and "harmonious" task periodicity.
Key concepts: Dynamic voltage scaling, Computer science, Energy consumption, Intuition, Voltage, Scheduling (production processes), Scaling, Task (project management)