Cluster-Wide Context Switch of Virtualized Jobs - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Reports (Research Report) Year : 2009

Cluster-Wide Context Switch of Virtualized Jobs

Abstract

Clusters are massively used through Resource Management Systems with a static allocation of resources for a bounded amount of time. Such an approach leads to a coarse-grain exploitation of the architecture and an increase of the job completion times since most of the scheduling policies rely on users estimates and do no consider the real needs of applications in terms of both resources and times. Encapsulating jobs into VMs enables to implement finer scheduling policies through cluster-wide context switches: a permutation between VMs present in the cluster. It results a more flexible use of cluster resources and relieve end-users of the burden of dealing with time estimates. Leveraging the Entropy framework, this paper introduces a new infrastructure enabling cluster-wide context switches of virtualized jobs to improve resource management. As an example, we propose a scheduling policy to execute a maximum number of jobs simultaneously, and uses VM operations such as migrations, suspends and resumes to resolve underused and overloaded situations. We show through experiments that such an approach improves resource usage and reduces the overall duration of jobs. Moreover, as the cost of each action and the dependencies between them is considered, Entropy reduces, the duration of each cluster-wide context switch by performing a minimum number of actions, in the most efficient way.
Fichier principal
Vignette du fichier
RR-6929.pdf (497.79 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

inria-00383325 , version 1 (12-05-2009)

Identifiers

  • HAL Id : inria-00383325 , version 1

Cite

Fabien Hermenier, Adrien Lebre, Jean-Marc Menaud. Cluster-Wide Context Switch of Virtualized Jobs. [Research Report] RR-6929, INRIA. 2009. ⟨inria-00383325⟩
569 View
313 Download

Share

Gmail Facebook X LinkedIn More