Energy-Aware Scheduling using Dynamic Voltage-Frequency Scaling

TL;DR

This paper reviews and extends energy-aware scheduling algorithms that utilize dynamic voltage-frequency scaling (DVFS) in distributed systems, supported by experimental evaluations on numerous task graphs.

Contribution

It provides a comprehensive analysis of recent DVFS-based scheduling algorithms and develops new approaches, validated through extensive experiments.

Findings

Effective energy savings demonstrated in experiments

Improved scheduling efficiency with DVFS techniques

Scalability shown across various task graph sizes

Abstract

The energy consumption issue in distributed computing systems has become quite critical due to environmental concerns. In response to this, many energy-aware scheduling algorithms have been developed primarily by using the dynamic voltage-frequency scaling (DVFS) capability incorporated in recent commodity processors. The majority of these algorithms involve two passes: schedule generation and slack reclamation. The latter is typically achieved by lowering processor frequency for tasks with slacks. In this article, we study the latest papers in this area and develop them. This study has been evaluated based on results obtained from experiments with 1,500 randomly generated task graphs.