Autonomous and Energy-Aware Management of Large-Scale Cloud Infrastructures - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2012

Autonomous and Energy-Aware Management of Large-Scale Cloud Infrastructures

Abstract

With the advent of cloud computing and the need for increasing amount of computing power, cloud infrastructure providers are now facilitating the deployment of large-scale data centers. In order to efficiently manage such environments three important properties have to be fulfilled by their resource management frameworks: (1) scalability; (2) autonomy (i.e. self-organization and healing); (3) energy-awareness. However, existing open-source cloud management stacks (e.g. Eucalyptus, Nimbus, OpenNebula, OpenStack) have a high degree of centralization and limited power management support. In this context, this PhD thesis focuses on more scalable, autonomic, and energy-aware resource management frameworks for large-scale cloud infrastructures. Particularly, a novel virtual machine (VM) management system based on a self-organizing hierarchical architecture called Snooze is proposed. In order to conserve energy, Snooze automatically transitions idle servers into a low-power mode (e.g. suspend). To favor idle times the system integrates a nature-inspired VM consolidation algorithm based on the Ant Colony Optimization (ACO).
Fichier principal
Vignette du fichier
phdforum.pdf (178.31 Ko) Télécharger le fichier
Origin Files produced by the author(s)
Loading...

Dates and versions

hal-00676295 , version 1 (20-07-2012)

Identifiers

  • HAL Id : hal-00676295 , version 1

Cite

Eugen Feller, Christine Morin. Autonomous and Energy-Aware Management of Large-Scale Cloud Infrastructures. PhD Forum of the 26th IEEE International Parallel & Distributed Processing Symposium (IPDPS PhD Forum), May 2012, Shanghai, China. ⟨hal-00676295⟩
515 View
384 Download

Share

Gmail Mastodon Facebook X LinkedIn More