Concepedia

Power Aware Scheduling of Bag-of-Tasks Applications with Deadline Constraints on DVS-enabled Clusters

Kyong Hoon Kim, Rajkumar Buyya, Jong Kim

2007 · 317 citations · 27 references

TL;DR

Power‑aware scheduling in clusters is crucial for reducing electricity costs and enhancing reliability, especially as commodity processors now support multiple voltage levels that enable DVS to lower power consumption. The paper proposes power‑aware scheduling algorithms for bag‑of‑tasks applications with deadline constraints on DVS‑enabled clusters to minimize power while meeting user deadlines. The scheduling scheme accounts for task deadlines and implements both time‑shared and space‑shared policies to allocate voltage levels accordingly. Simulation results show the proposed algorithms significantly reduce power consumption compared to static voltage schemes.

Abstract

Power-aware scheduling problem has been a recent issue in cluster systems not only for operational cost due to electricity cost, but also for system reliability. As recent commodity processors support multiple operating points under various supply voltage levels, Dynamic Voltage Scaling (DVS) scheduling algorithms can reduce power consumption by controlling appropriate voltage levels. In this paper, we provide power-aware scheduling algorithms for bag-of-tasks applications with deadline constraints on DVS-enabled cluster systems in order to minimize power consumption as well as to meet the deadlines specified by application users. A bag-of-tasks application should finish all the sub-tasks before the deadline, so that the DVS scheduling scheme should consider the deadline as well. We provide the DVS scheduling algorithms for both time-shared and space-shared resource sharing policies. The simulation results show that the proposed algorithms reduce much power consumption compared to static voltage schemes.