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Performance-controlled server consolidation for virtualized data centers with multi-tier applications.

Authors :
Wang, Yefu
Wang, Xiaorui
Source :
Sustainable Computing: Informatics & Systems; Mar2014, Vol. 4 Issue 1, p52-65, 14p
Publication Year :
2014

Abstract

Abstract: Modern data centers must provide performance assurance for complex system software such as multi-tier web applications. In addition, the power consumption of data centers needs to be minimized to reduce operating costs and avoid system overheating. Various power-efficient performance management strategies have been proposed based on dynamic voltage and frequency scaling (DVFS). Virtualization technologies have also made it possible to consolidate multiple virtual machines (VMs) onto a smaller number of active physical servers for even greater power savings, but at the cost of a higher overhead. This paper proposes a performance-controlled power optimization solution for virtualized server clusters with multi-tier applications. While most existing work relies on either DVFS or server consolidation in a separate manner, our solution utilizes both strategies for maximized power savings by integrating feedback control with optimization strategies. At the application level, a novel multi-input–multi-output controller is designed to achieve the desired performance for applications spanning multiple VMs, on a short time scale, by reallocating the CPU resources and conducting DVFS. At the cluster level, a power optimizer is proposed to incrementally consolidate VMs onto the most power-efficient servers on a longer time scale. Empirical results on a hardware testbed demonstrate that our solution outperforms pMapper, a state-of-the-art server consolidation algorithm, by having greater power savings and smaller consolidation overheads while achieving the required application performance. Extensive simulation results, based on a trace file of 5415 real servers, demonstrate the efficacy of our solution in large-scale data centers. [Copyright &y& Elsevier]

Details

Language :
English
ISSN :
22105379
Volume :
4
Issue :
1
Database :
Supplemental Index
Journal :
Sustainable Computing: Informatics & Systems
Publication Type :
Academic Journal
Accession number :
95384870
Full Text :
https://doi.org/10.1016/j.suscom.2014.02.001