SaaS enabled admission control for MCMC simulation in cloud computing infrastructures

J. L. Vázquez-Poletti*, R. Moreno-Vozmediano, R. Han, W. Wang, I. M. Llorente

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)

Abstract

Markov Chain Monte Carlo (MCMC) methods are widely used in the field of simulation and modelling of materials, producing applications that require a great amount of computational resources. Cloud computing represents a seamless source for these resources in the form of HPC. However, resource over-consumption can be an important drawback, specially if the cloud provision process is not appropriately optimized. In the present contribution we propose a two-level solution that, on one hand, takes advantage of approximate computing for reducing the resource demand and on the other, uses admission control policies for guaranteeing an optimal provision to running applications.

Original languageEnglish
Pages (from-to)88-97
Number of pages10
JournalComputer Physics Communications
Volume211
DOIs
Publication statusPublished - 1 Feb 2017
Externally publishedYes

Keywords

  • Admission control
  • Cloud computing
  • PaaS
  • SaaS

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