English

Distributed virtual machine consolidation: A systematic mapping study

Distributed, Parallel, and Cluster Computing 2018-03-12 v1

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.

Keywords

Cite

@article{arxiv.1803.03094,
  title  = {Distributed virtual machine consolidation: A systematic mapping study},
  author = {Adnan Ashraf and Benjamin Byholm and Ivan Porres},
  journal= {arXiv preprint arXiv:1803.03094},
  year   = {2018}
}

Comments

The manuscript has been accepted for publication in Computer Science Review