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Distributed virtual machine consolidation: A systematic mapping study

Adnan Ashraf, Benjamin Byholm, Ivan Porres, Distributed virtual machine consolidation: A systematic mapping study. Computer Science Review 28C, 118–130, 2018.

Abstract:

Background: Virtual Machine (VM) consolidation is an effective technique to improve resource utilization and reduce energy footprint in cloud data centers. It can be implemented in a centralized or a distributed fashion. Distributed VM consolidation approaches are currently gaining popularity because they are often more scalable than their centralized counterparts and they avoid a single point of failure.

Objective: To present a comprehensive, unbiased overview of the state-of-the-art on distributed VM consolidation approaches.

Method: A Systematic Mapping Study (SMS) of the existing distributed VM consolidation approaches.

Results: 19 papers on distributed VM consolidation categorized in a variety of ways. The results show that the existing distributed VM consolidation approaches use four types of algorithms, optimize a number of different objectives, and are often evaluated with experiments involving simulations.

Conclusion: There is currently an increasing amount of interest on developing and evaluating novel distributed VM consolidation approaches. A number of research gaps exist where the focus of future research may be directed.

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BibTeX entry:

@ARTICLE{jAsByPo18a,
  title = {Distributed virtual machine consolidation: A systematic mapping study},
  author = {Ashraf, Adnan and Byholm, Benjamin and Porres, Ivan},
  journal = {Computer Science Review},
  volume = {28C},
  pages = {118–130},
  year = {2018},
  keywords = {Cloud computing, Data center, Virtual machine, Consolidation, Placement, Energy-efficiency},
  ISSN = {1574-0137},
}

Belongs to TUCS Research Unit(s): Software Engineering Laboratory (SE Lab)

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