An overlay-based data mining architecture tolerant to physical network disruptions

Katsuya Suto, Hiroki Nishiyama, Nei Kato, Kimihiro Mizutani, Osamu Akashi, Atsushi Takahara

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

Management scheme for highly scalable big data mining has not been well studied in spite of the fact that big data mining provides many valuable and important information for us. An overlay-based parallel data mining architecture, which executes fully distributed data management and processing by employing the overlay network, can achieve high scalability. However, the overlay-based parallel mining architecture is not capable of providing data mining services in case of the physical network disruption that is caused by router/communication line breakdowns because numerous nodes are removed from the overlay network. To cope with this issue, this paper proposes an overlay network construction scheme based on node location in physical network, and a distributed task allocation scheme using overlay network technology. The numerical analysis indicates that the proposed schemes considerably outperform the conventional schemes in terms of service availability against physical network disruption.

Original languageEnglish
Article number6832507
Pages (from-to)292-301
Number of pages10
JournalIEEE Transactions on Emerging Topics in Computing
Volume2
Issue number3
DOIs
Publication statusPublished - 2014 Sep 1

Keywords

  • Big data mining
  • neighbor selection
  • overlay network
  • physical network disruption
  • service availability
  • task allocation

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications

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