Revisiting virtual machine consolidation to save resources and energy in heterogeneous production cloud infrastructures

Due to some overprovisioning policies and variable usage, data centers in production can face low average resource utilization. This can result in a waste of underused servers and energy. In this context, virtual machine (VM) consolidation combined with shutdown policies can be a pertinent approach for improving resource utilization and reducing energy consumption of the entire cloud infrastructure. However, VM consolidation requires expensive migration techniques, which can potentially affect performance. Consolidation of workload has been proposed and studied as a core capability since the invention of the Cloud. But after two decades of deployment of Cloud infrastructures, VM consolidation is still rarely used in production for small and large-scale environments. In this article, we explore and revisit the potential of savings that can be achieved through a versatile and efficient Virtual Machine consolidation in small and large-scale production infrastructures through usage analysis of two Cloud providers infrastructures. We show that potential benefits in terms of saved cloud resources and energy usage reduction can occur for systems in production.

Authors

Institutions

Publication Details

Journal
The International Journal of High Performance Computing Applications
Published
2025-12-18
DOI
https://doi.org/10.1177/10943420251399694
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Revisiting virtual machine consolidation to save resources and energy in heterogeneous production cloud infrastructures

Vladimir Ostapenco, Benjamin Fichel, Anne‐Cécile Orgerie, Laurent Lefèvre et al.
The International Journal of High Performance Computing Applications
Cloud Computing and Resource Management
article

Revisiting virtual machine consolidation to save resources and energy in heterogeneous production cloud infrastructures

Vladimir Ostapenco, Benjamin Fichel, Anne‐Cécile Orgerie, Laurent Lefèvre, Rémi Grivel, Eddy Caron, Simon Lambert
article en

Abstract

Due to some overprovisioning policies and variable usage, data centers in production can face low average resource utilization. This can result in a waste of underused servers and energy. In this context, virtual machine (VM) consolidation combined with shutdown policies can be a pertinent approach for improving resource utilization and reducing energy consumption of the entire cloud infrastructure. However, VM consolidation requires expensive migration techniques, which can potentially affect performance. Consolidation of workload has been proposed and studied as a core capability since the invention of the Cloud. But after two decades of deployment of Cloud infrastructures, VM consolidation is still rarely used in production for small and large-scale environments. In this article, we explore and revisit the potential of savings that can be achieved through a versatile and efficient Virtual Machine consolidation in small and large-scale production infrastructures through usage analysis of two Cloud providers infrastructures. We show that potential benefits in terms of saved cloud resources and energy usage reduction can occur for systems in production.

The International Journal of High Performance Computing Applications
Université Claude Bernard Lyon 1 (FR), École Normale Supérieure de Lyon (FR), Centre National de la Recherche Scientifique (FR), Online Computer Library Center (US), École nationale d'ingénieurs de Brest (FR), Université de Lyon (FR), Institut de Recherche en Informatique et Systèmes Aléatoires (FR), Centre d'Énergétique et de Thermique de Lyon (FR), Forum Réfugiés - Cosi (FR), Université de Rennes (FR)
Openalex Percentile: Top 47%
Cloud Computing and Resource Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.