Energy Management in IaaS Clouds: A Holistic Approach
type: Dataset
description: Energy efficiency has now become one of the major design constraints for current and future cloud data center operators. One way to conserve energy is to transition idle servers into a lower power-state (e.g. suspend). Therefore, virtual machine (VM) placement and dynamic VM scheduling algorithms are proposed to facilitate the creation of idle times. However, these algorithms are rarely integrated in a holistic approach and experimentally evaluated in a realistic environment. In this paper we present the energy management algorithms and mechanisms of a novel holistic energy-aware VM management framework for private clouds called Snooze. We conduct an extensive evaluation of the energy and performance implications of our system on 34 power-metered machines of the Grid'5000 experimentation testbed under dynamic web workloads. The results show that the energy saving mechanisms allow Snooze to dynamically scale data center energy consumption proportionally to the load, thus achieving substantial energy savings with only limited impact on application performance.
identifier: Report N°: RR-7946
issued: 2026-05-20T12:18:36.748660
language: en
modified: 2026-05-20T12:18:36.748668
contact point: Organization
  fn: CCSD
keyword: cloud-computing
keyword: consolidation
keyword: energy-management
keyword: infoeu-reposemanticsreport
keyword: infoinfo-dccomputer-science-csdistributed-parallel-and-cluster-computing-csdc
keyword: live-migration
keyword: relocation
keyword: reports
keyword: virtualization
landing page: https://inria.hal.science/hal-00692236

Energy Management in IaaS Clouds: A Holistic Approach
type: Distribution
format: HTML
issued: 2026-05-20T12:18:36.776424
modified: 2026-05-20T12:18:36.714573
access URL: https://inria.hal.science/hal-00692236

test_moissonnage_selune
type: Agent