Virtual machine placement with (m, n)-fault tolerance in cloud data center

Ao Zhou, Shangguang Wang, Ching Hsien Hsu, Myung Ho Kim, Kok seng Wong

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Scalable computing resources are provided via the Internet in the cloud computing environment. A growing number of application providers begin to deploy their applications in cloud to save the infrastructure maintaince cost. The probability of node failures cannot be nontrivial due to a great quantity of nodes in the cloud data center. To address the problem, the virtual machine replication technique is extensively adopted in the cloud system to enhance the application/service reliability. K-fault tolerance is a typical replication strategy employed in cloud. However, currently proposed K-fault tolerance replication strategies cannot achieve the best effect due to the ignorance of switch failure. In this paper, we study to design a (m, n)-fault tolerance virtual machine placement algorithm to solve the problem. Firstly, we formulate the problem as an integer linear programming problem, and prove that the problem is NP-hard. Secondly, we extensively employ differential evolution (DE) algorithm to solve the integer linear programming problem. Finally, experiments are conducted to study the effectiveness of our algorithm, and the simulation results demonstrate that our algorithm outperforms other algorithms in reliability enhancement.

Original languageEnglish
Pages (from-to)1-13
Number of pages13
JournalCluster Computing
DOIs
Publication statusAccepted/In press - Dec 8 2017

Keywords

  • Cloud computing
  • Data center network
  • Fault tolerance
  • Virtual machine placement

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications

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