An intelligent residual resource monitoring scheme in cloud computing environments

Jong Beom Lim, Heonchang Yu, Joon Min Gil

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Recently, computational intelligence has received a lot of attention from researchers due to its potential applications to artificial intelligence. In computer science, computational intelligence refers to a machine's ability to learn how to compete various tasks, such as making observations or carrying out experiments. We adopted a computational intelligence solution to monitoring residual resources in cloud computing environments. The proposed residual resource monitoring scheme periodically monitors the cloud-based host machines, so that the post migration performance of a virtual machine is as consistent with the pre-migration performance as possible. To this end, we use a novel similarity measure to find the best target host to migrate a virtual machine to. The design of the proposed residual resource monitoring scheme helps maintain the quality of service and service level agreement during the migration. We carried out a number of experimental evaluations to demonstrate the effectiveness of the proposed residual resource monitoring scheme. Our results show that the proposed scheme intelligently measures the similarities between virtual machines in cloud computing environments without causing performance degradation, whilst preserving the quality of service and service level agreement.

Original languageEnglish
Pages (from-to)1480-1493
Number of pages14
JournalJournal of Information Processing Systems
Volume14
Issue number6
DOIs
Publication statusPublished - 2018 Jan 1

Keywords

  • Cloud computing
  • Clustering
  • Computational intelligence
  • Resource monitoring

ASJC Scopus subject areas

  • Software
  • Information Systems

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