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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. TUCS Technical Reports 1171, TUCS, 2016.

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.

Files:

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BibTeX entry:

@TECHREPORT{tAsByPo16a,
  title = {Distributed Virtual Machine Consolidation: A Systematic Mapping Study},
  author = {Ashraf, Adnan and Byholm, Benjamin and Porres, Ivan},
  number = {1171},
  series = {TUCS Technical Reports},
  publisher = {TUCS},
  year = {2016},
  keywords = {Cloud computing, Data center, Virtual machine, Consolidation, Placement, Energy-efficiency},
  ISBN = {978-952-12-3487-3},
}

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

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