Distributed virtual machine consolidation: A systematic mapping study

TL;DR

This paper systematically reviews distributed virtual machine consolidation techniques, highlighting their algorithms, objectives, evaluation methods, and identifying research gaps for future advancements.

Contribution

It provides a comprehensive overview of the current state-of-the-art in distributed VM consolidation through a systematic mapping study.

Findings

19 papers categorized on distributed VM consolidation

Use of four types of algorithms in approaches

Predominant evaluation through simulations

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.