Energy-efficient dynamic consolidation of virtual machines in big data centers

Shuting Xu, Chase Q. Wu, Aiqin Hou, Yongqiang Wang, Meng Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

There is a rapidly growing demand for computing power driven by big data applications, which is typically met by constructing large-scale data centers provisioning virtualized resources. Such data centers consume an enormous amount of energy, resulting in high operational cost and carbon dioxide emission. Meanwhile, cloud providers need to ensure Quality of Service (QoS) in the computing solution delivered to their customers, and hence must consider the power-performance trade-off. We propose a virtual machine (VM) consolidation optimization framework, consisting of three optimization processes in big data centers: (i) VM allocation, (ii) overloaded physical machine (PM) detection and consolidation, and (iii) underloaded PM detection and consolidation. We show that the optimization problem is NP-complete, and design a resource management scheme that integrates three algorithms, one for each optimization process. We implement and evaluate the proposed resource management scheme in CloudSim and conduct simulations on a real workload trace of PlanetLab. Extensive simulation results show that the proposed solution yields up to 21.5% reduction in energy consumption, 34.2% reduction in performance degradation due to migration, 70.2% reduction in SLA violation time per active host, and 68% reduction in Energy and SLA Violations (ESV), respectively, in comparison with state-of-the-art solutions.

Original languageEnglish (US)
Title of host publicationGreen, Pervasive, and Cloud Computing - 12th International Conference, GPC 2017, Proceedings
EditorsMan Ho Allen Au, Kim-Kwang Raymond Choo, Kuan-Ching Li, Arcangelo Castiglione, Francesco Palmieri
PublisherSpringer Verlag
Pages191-206
Number of pages16
ISBN (Print)9783319571850
DOIs
StatePublished - 2017
Event12th International Conference on Green, Pervasive and Cloud Computing, GPC 2017 - Cetara, Italy
Duration: May 11 2017May 14 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10232 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th International Conference on Green, Pervasive and Cloud Computing, GPC 2017
Country/TerritoryItaly
CityCetara
Period5/11/175/14/17

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

Keywords

  • Big data centers
  • Energy consumption
  • VM consolidation

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