Autonomic power and performance management for computing systems

Bithika Khargharia, Salim Hariri, Mazin S. Yousif

Research output: Contribution to journalArticlepeer-review

62 Scopus citations

Abstract

With the increased complexity of platforms, the growing demand of applications and data centers' servers sprawl, power consumption is reaching unsustainable limits. The need to improved power management is becoming essential for many reasons including reduced power consumption & cooling, improved density, reliability & compliance with environmental standards. This paper presents a theoretical framework and methodology for autonomic power and performance management in e-business data centers. We optimize for power and performance (performance-per-watt) at each level of the hierarchy while maintaining scalability. We adopt mathematically-rigorous optimization approach to minimize power while meeting performance constraints. Our experimental results show around 72% savings in power while maintaining performance as compared to static power management techniques and 69.8% additional savings with both global and local optimizations.

Original languageEnglish (US)
Pages (from-to)167-181
Number of pages15
JournalCluster Computing
Volume11
Issue number2
DOIs
StatePublished - Jun 2008

Keywords

  • Autonomic management
  • Optimization
  • Power

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications

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