An efficient and energy-aware cloud consolidation algorithm for multimedia big data applications

Jong Beom Lim, Heonchang Yu, Joon Min Gil

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

It is well known that cloud computing has many potential advantages over traditional distributed systems. Many enterprises can build their own private cloud with open source infrastructure as a service (IaaS) frameworks. Since enterprise applications and data are migrating to private cloud, the performance of cloud computing environments is of utmost importance for both cloud providers and users. To improve the performance, previous studies on cloud consolidation have been focused on live migration of virtual machines based on resource utilization. However, the approaches are not suitable for multimedia big data applications. In this paper, we reveal the performance bottleneck of multimedia big data applications in cloud computing environments and propose a cloud consolidation algorithm that considers application types. We show that our consolidation algorithm outperforms previous approaches.

Original languageEnglish
Article number184
JournalSymmetry
Volume9
Issue number9
DOIs
Publication statusPublished - 2017 Sep 1

Fingerprint

consolidation
Consolidation
multimedia
Multimedia
Cloud computing
Cloud Computing
Energy
energy
Virtual Machine
Industry
Open Source
Migration
Distributed Systems
Infrastructure
Big data
Resources
resources

Keywords

  • Big data
  • Cloud computing
  • Cloud consolidation
  • Multimedia application
  • Virtual machine

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Chemistry (miscellaneous)
  • Mathematics(all)
  • Physics and Astronomy (miscellaneous)

Cite this

An efficient and energy-aware cloud consolidation algorithm for multimedia big data applications. / Lim, Jong Beom; Yu, Heonchang; Gil, Joon Min.

In: Symmetry, Vol. 9, No. 9, 184, 01.09.2017.

Research output: Contribution to journalArticle

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