JOURNAL ARTICLE

Workload-aware Power Management of Cluster Systems

Abstract

Along with the increased awareness of energy cost, power management becomes a big issue for clusters. In this study, we investigate the workload aware power management techniques for cluster systems and propose a new power management policy. The considered power management techniques are dynamic workload consolidation and usage of dynamic power range enabled by low power states on servers. The power management policy has been implemented on OpenPBS with Maui, which reduces about ten percent power consumption and optimizes workload distribution to lower the impact on performance.

Keywords:
Workload Power management Computer science Server Power consumption Dynamic demand Energy consumption Power (physics) Cluster (spacecraft) Reliability engineering Resource management (computing) Energy management Distributed computing Operating system Engineering Energy (signal processing) Electrical engineering

Metrics

2
Cited By
0.70
FWCI (Field Weighted Citation Impact)
15
Refs
0.82
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Cloud Computing and Resource Management
Physical Sciences →  Computer Science →  Information Systems
Distributed and Parallel Computing Systems
Physical Sciences →  Computer Science →  Computer Networks and Communications
Parallel Computing and Optimization Techniques
Physical Sciences →  Computer Science →  Hardware and Architecture

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